1. Adaptive Pinning Control of Deteriorated Nonlinear Coupling Networks With Circuit Realization
Xiao-Zheng Jin; Guang-Hong Yang; Wei-Wei Che
Page(s): 1345 - 1355
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6222060
2. Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines
Siamak Mehrkanoon; Tillmann Falck; Johan A. K. Suykens
Page(s): 1356 - 1367
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6224185
3. Exponential Synchronization of Neural Networks With Discrete and Distributed Delays Under Time-Varying Sampling
Zheng-Guang Wu; Peng Shi; Hongye Su; Jian Chu
Page(s): 1368 - 1376
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6227362
4. Convergence and Rate Analysis of Neural Networks for Sparse Approximation
Aurèle Balavoine; Justin Romberg; Christopher J. Rozell
Page(s): 1377 - 1389
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6227360
5. In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines
Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella
Page(s): 1390 - 1406
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6228541
6. Robust Exponential Stability of Uncertain Stochastic Neural Networks With Distributed Delays and Reaction-Diffusions
Jianping Zhou; Shengyuan Xu; Baoyong Zhang; Yun Zou; Hao Shen
Page(s): 1407 - 1416
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6228542
7. Online Kernel-Based Learning for Task-Space Tracking Robot Control
Duy Nguyen-Tuong; Jan Peters
Page(s): 1417 - 1425
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6230657
8. Memristor Bridge Synapse-Based Neural Network and Its Learning
Shyam Prasad Adhikari; Changju Yang; Hyongsuk Kim; Leon O. Chua
Page(s): 1426 - 1435
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6232461
9. Efficient Sparse Modeling With Automatic Feature Grouping
Leon Wenliang Zhong; James T. Kwok
Page(s): 1436 - 1447
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6238378
10. Hierarchical Approach for Multiscale Support Vector Regression
Francesco Bellocchio; Stefano Ferrari; Vincenzo Piuri; Nunzio Alberto Borghese
Page(s): 1448 - 1460
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6238377
11. Discretized-Vapnik-Chervonenkis Dimension for Analyzing Complexity of Real Function Classes
Chao Zhang; Wei Bian; Dacheng Tao; Weisi Lin
Page(s): 1461 - 1472
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6239601
12. Limit Set Dichotomy and Multistability for a Class of Cooperative Neural Networks With Delays
Mauro Di Marco; Mauro Forti; Massimo Grazzini; Luca Pancioni
Page(s): 1473 - 1485
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6241435
13. Adaptive Visual and Auditory Map Alignment in Barn Owl Superior Colliculus and Its Neuromorphic Implementation
Juan Huo; Alan Murray; Dongqing Wei
Page(s): 1486 - 1497
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6255791
14. Bidirectional Extreme Learning Machine for Regression Problem and Its Learning Effectiveness
Yimin Yang; Yaonan Wang; Xiaofang Yuan
Page(s): 1498 - 1505
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6222007
15. Enhancing Weak Signal Transmission Through a Feedforward Network
Xiaoming Liang; Liang Zhao; Zonghua Liu
Page(s): 1506 - 1512
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6227359
Friday, August 17, 2012
Thursday, August 16, 2012
ECoS toolbox API?
Is anyone interested in an ECoS DLL / API? I'm thinking of wrapping the functionality in the command-line ECoS Toolbox up in a DLL and providing an API so that people could include EFuNN and SECoS in their own programs. Is this a worthwhile use of my time? Would anyone use it?
Wednesday, August 15, 2012
Reminder: paper submission deadline for CEC 2013
A reminder that the deadline for submitting papers to the IEEE Congress on Evolutionary Computation (CEC) 2013 is February 15, 2013. This conference will be held in Cancun, Mexico, June 20-23, 2013.
Tuesday, August 14, 2012
Identifying bats with ANN
An interesting paper has just come out in the Journal of Applied Ecology, which describes how ANN were used to identify thirty-four European species of bats based on their echolocation calls. This is a challenging problem, because the calls within any bat species can vary quite a lot, depending on what the bat is doing. For example, the calls that a bat uses while hunting are different to the calls that a bat uses while commuting to a hunting ground. The work described in this paper has several good features.
Firstly, they used a hierarchy of MLP ensembles to identify the species. First a level of MLP identified the geographic region (out of six) that the bat came from. Then a second level was used to identify the genus (out of seven) of the bat. Finally, an ensemble of species-specific MLP identified the species itself.
Secondly, they used a large data set to train the MLP, and performed a thorough data analysis to identify the significant features. Rather than just cramming every acoustic feature through the MLP and hoping for the best, they only used the most significant twenty-four.
Finally, they incorporated the classifiers into software called iBatsID that is freely available for anyone to use.
The authors reported a range of classification accuracies across the species, from a high of 100% to a low of 56.5%. They say that "This is almost certainly the results of our eANN [ensemble ANN] dealing with many more species". I think they're wrong when they say that, because the point of using ensembles is that the individual members of the ensemble can be highly specialised for a particular class. I suspect that the problem may be that the features they selected were not as useful for classifying the poorly-recognised species: rather than using the same twenty-four parameters for all thirty-four species, they might have gotten better results by selecting acoustic parameters for each species. Also, from the diagram (Figure 3 in the paper) it looks like they used the outputs of the regional and genus networks only to decide which groups of species MLP to use. An alternative would have been to use the output of the regional and genus MLP as input features for the following levels (similar to my approach in this paper), which would have added some more information into the classification process and probably boosted accuracy.
A final problem with this paper is that they have excluded a lot of the technical details about constructing and training the ANN, and about exactly how the different levels in the hierarchy interacted. This is probably because it is an ecology paper, not an ANN paper.
Overall, it's an interesting application, and I'm looking forward to seeing more work done on this problem in the future.
Firstly, they used a hierarchy of MLP ensembles to identify the species. First a level of MLP identified the geographic region (out of six) that the bat came from. Then a second level was used to identify the genus (out of seven) of the bat. Finally, an ensemble of species-specific MLP identified the species itself.
Secondly, they used a large data set to train the MLP, and performed a thorough data analysis to identify the significant features. Rather than just cramming every acoustic feature through the MLP and hoping for the best, they only used the most significant twenty-four.
Finally, they incorporated the classifiers into software called iBatsID that is freely available for anyone to use.
The authors reported a range of classification accuracies across the species, from a high of 100% to a low of 56.5%. They say that "This is almost certainly the results of our eANN [ensemble ANN] dealing with many more species". I think they're wrong when they say that, because the point of using ensembles is that the individual members of the ensemble can be highly specialised for a particular class. I suspect that the problem may be that the features they selected were not as useful for classifying the poorly-recognised species: rather than using the same twenty-four parameters for all thirty-four species, they might have gotten better results by selecting acoustic parameters for each species. Also, from the diagram (Figure 3 in the paper) it looks like they used the outputs of the regional and genus networks only to decide which groups of species MLP to use. An alternative would have been to use the output of the regional and genus MLP as input features for the following levels (similar to my approach in this paper), which would have added some more information into the classification process and probably boosted accuracy.
A final problem with this paper is that they have excluded a lot of the technical details about constructing and training the ANN, and about exactly how the different levels in the hierarchy interacted. This is probably because it is an ecology paper, not an ANN paper.
Overall, it's an interesting application, and I'm looking forward to seeing more work done on this problem in the future.
Monday, August 13, 2012
The problem with academic journals 6
In my previous posts on academic journals (see here, here, here, here, here, and here) I've discussed the major problem with academic journals in the context of the huge cost of accessing the content that the journals receive for free, as well as the importance of open-access journals. This post is concerned with another problem that is becoming apparent with journals: the declining acceptance rate for papers submitted to journals, in attempts to foster an image of exclusivity and quality.
A recent editorial by David Wardle describes a quantitative analysis he performed that compared the acceptance rates of four top-ranked ecological journals with the large open-access journal PLoS One, along with the citation rate of papers published in each. What he found was that the four traditional journals accepted less than 20% of the paper submitted to them, while PLoS One accepted around 69%. However, papers that are published in PLoS One are cited more than papers published in one of the traditional journals. His argument was that the traditional journals rejected papers that were of good scientific quality (that is, they described good work) but were not "worthy" of publication in such "august" journals, with the editors using the excuse that limited page space meant that there wasn't room to print the papers, even though they were quite good. He then goes on to explain that this exclusivity was motivated by a desire to increase the perception of quality of the journals. That is, the editors are trying to foster the impression that the journals must be really good, because they're really picky about which papers they publish.
But, the ultimate measure of the quality of a paper is how often it is cited, as that reflects how useful it is to other scientists, and papers published in the less-exclusive open-access journals are cited more. Thus, the concept that journals with low acceptance rates publish better papers is fatally flawed: these journals are rejecting papers that are scientifically sound and are useful to other scientists.
This leads me to think that the only reason the top journals are the top journals are because people think they are. If someone wants an authoritative citation to back up a statement they make in a paper, they will cite a paper in Nature or Science if they can, because these are the top journals (this doesn't happen much in computational intelligence, because very few papers in this field are published in Nature or Science). But the conclusion of Wardle's study is that acceptance rate is not a reliable metric of the quality of a journal. If anything, it is a measure of the snobbery of a journal.
The purpose of peer review (and of reviewers) is as a crap-filter for papers, to keep work that is incorrectly done or poorly presented from entering the literature. But with exclusive journals, the peer reviewers seem to be spending more time deciding which papers are significant enough to be published in the journal, rather than trying to identify flaws in the work. The whole thing reminds me of the reason the great physicist Richard Feynman quit the US National Academy of Science: because they spent most of their time deciding who was "worthy" of joining the Academy.
Not so long ago, we had to consider the quality of journals because it wasn't feasible to track the impact of a single paper. Now, with tools like Google Scholar, we can track the citation histories of individual papers. In short, the journal in which a paper is published is no longer that important: the usefulness, the contribution of the paper is what is important. By the same token, the quality of an academic is not measured by which institution they work for, but by their contributions. Unfortunately, the bean-counters who make the hiring and promotion decisions, and who make decisions on who gets competitive research funding, haven't grasped this concept yet.
Exclusive journals do not make a good contribution to science, as they keep too much useful material out of the public eye for too long: peer-reviewed open-access journals, with their more liberal acceptance rates, are more important then ever in this situation.
A recent editorial by David Wardle describes a quantitative analysis he performed that compared the acceptance rates of four top-ranked ecological journals with the large open-access journal PLoS One, along with the citation rate of papers published in each. What he found was that the four traditional journals accepted less than 20% of the paper submitted to them, while PLoS One accepted around 69%. However, papers that are published in PLoS One are cited more than papers published in one of the traditional journals. His argument was that the traditional journals rejected papers that were of good scientific quality (that is, they described good work) but were not "worthy" of publication in such "august" journals, with the editors using the excuse that limited page space meant that there wasn't room to print the papers, even though they were quite good. He then goes on to explain that this exclusivity was motivated by a desire to increase the perception of quality of the journals. That is, the editors are trying to foster the impression that the journals must be really good, because they're really picky about which papers they publish.
But, the ultimate measure of the quality of a paper is how often it is cited, as that reflects how useful it is to other scientists, and papers published in the less-exclusive open-access journals are cited more. Thus, the concept that journals with low acceptance rates publish better papers is fatally flawed: these journals are rejecting papers that are scientifically sound and are useful to other scientists.
This leads me to think that the only reason the top journals are the top journals are because people think they are. If someone wants an authoritative citation to back up a statement they make in a paper, they will cite a paper in Nature or Science if they can, because these are the top journals (this doesn't happen much in computational intelligence, because very few papers in this field are published in Nature or Science). But the conclusion of Wardle's study is that acceptance rate is not a reliable metric of the quality of a journal. If anything, it is a measure of the snobbery of a journal.
The purpose of peer review (and of reviewers) is as a crap-filter for papers, to keep work that is incorrectly done or poorly presented from entering the literature. But with exclusive journals, the peer reviewers seem to be spending more time deciding which papers are significant enough to be published in the journal, rather than trying to identify flaws in the work. The whole thing reminds me of the reason the great physicist Richard Feynman quit the US National Academy of Science: because they spent most of their time deciding who was "worthy" of joining the Academy.
Not so long ago, we had to consider the quality of journals because it wasn't feasible to track the impact of a single paper. Now, with tools like Google Scholar, we can track the citation histories of individual papers. In short, the journal in which a paper is published is no longer that important: the usefulness, the contribution of the paper is what is important. By the same token, the quality of an academic is not measured by which institution they work for, but by their contributions. Unfortunately, the bean-counters who make the hiring and promotion decisions, and who make decisions on who gets competitive research funding, haven't grasped this concept yet.
Exclusive journals do not make a good contribution to science, as they keep too much useful material out of the public eye for too long: peer-reviewed open-access journals, with their more liberal acceptance rates, are more important then ever in this situation.
Friday, August 10, 2012
Final reminder: IEEE CIS Facebook Photo Competition
The IEEE Computational Intelligence Society are running a photo
competition on Facebook. Go to http://www.watts.net.nz/CIS/contests/photo/2012/ or see the flyer below for further details.
The deadline is three weeks away!
The deadline is three weeks away!
Thursday, August 9, 2012
Reminder: paper submission deadline for IJCNN 2013
A reminder that the deadline for submitting papers to the IEEE International Joint Conference on Neural Networks (IJCNN) 2013 is February 1, 2013. This conference will be held in Dallas, Texas, August 4-9, 2013.
Wednesday, August 8, 2012
Reminder: paper submission deadline for EvoStar 2013
Tuesday, August 7, 2012
IEEE Transactions on Autonomous Mental Development: Volume 4, Issue 2, 2012
1. The “Interaction Engine”: A Common Pragmatic Competence Across Linguistic and Nonlinguistic Interactions
Pezzulo, G.
Page(s): 105 - 123
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6006515
2. Interactive Learning in Continuous Multimodal Space: A Bayesian Approach to Action-Based Soft Partitioning and Learning
Firouzi, H.; Ahmadabadi, M.N.; Araabi, B.N.; Amizadeh, S.; Mirian, M.S.; Siegwart, R.
Page(s): 124 - 138
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6032073
3. Tool–Body Assimilation of Humanoid Robot Using a Neurodynamical System
Nishide, S.; Tani, J.; Takahashi, T.; Okuno, H.G.; Ogata, T.
Page(s): 139 - 149
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6095595
4. Are Robots Appropriate for Troublesome and Communicative Tasks in a City Environment?
Hayashi, K.; Shiomi, M.; Kanda, T.; Hagita, N.
Page(s): 150 - 160
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6111246
5. Brain-Like Emergent Spatial Processing
Juyang Weng; Luciw, M.
Page(s): 161 - 185
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6095596
Pezzulo, G.
Page(s): 105 - 123
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6006515
2. Interactive Learning in Continuous Multimodal Space: A Bayesian Approach to Action-Based Soft Partitioning and Learning
Firouzi, H.; Ahmadabadi, M.N.; Araabi, B.N.; Amizadeh, S.; Mirian, M.S.; Siegwart, R.
Page(s): 124 - 138
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6032073
3. Tool–Body Assimilation of Humanoid Robot Using a Neurodynamical System
Nishide, S.; Tani, J.; Takahashi, T.; Okuno, H.G.; Ogata, T.
Page(s): 139 - 149
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6095595
4. Are Robots Appropriate for Troublesome and Communicative Tasks in a City Environment?
Hayashi, K.; Shiomi, M.; Kanda, T.; Hagita, N.
Page(s): 150 - 160
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6111246
5. Brain-Like Emergent Spatial Processing
Juyang Weng; Luciw, M.
Page(s): 161 - 185
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6095596
Monday, August 6, 2012
IEEE Transactions on Computational Intelligence and AI in Games: Volume 4, Issue 2, 2012
1. N-Grams and the Last-Good-Reply Policy Applied in General Game Playing
Tak, M.J.W.; Winands, M.H.M.; Bjornsson, Y.
Page(s): 73 - 83
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203383
2. A Discrete Evolutionary Model for Chess Players' Ratings
Fenner, T.; Levene, M.; Loizou, G.
Page(s): 84 - 93
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6168229
3. Evolving Multimodal Networks for Multitask Games
Schrum, J.; Miikkulainen, R.
Page(s): 94 - 111
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6179519
4. Bitwise-Parallel Reduction for Connection Tests
Browne, C.; Tavener, S.
Page(s): 112 - 119
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6185647
5. Information Set Monte Carlo Tree Search
Cowling, P.I.; Powley, E.J.; Whitehouse, D.
Page(s): 120 - 143
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203567
6. Benchmarks for Grid-Based Pathfinding
Sturtevant, N.R.
Page(s): 144 - 148
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6194296
Tak, M.J.W.; Winands, M.H.M.; Bjornsson, Y.
Page(s): 73 - 83
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203383
2. A Discrete Evolutionary Model for Chess Players' Ratings
Fenner, T.; Levene, M.; Loizou, G.
Page(s): 84 - 93
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6168229
3. Evolving Multimodal Networks for Multitask Games
Schrum, J.; Miikkulainen, R.
Page(s): 94 - 111
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6179519
4. Bitwise-Parallel Reduction for Connection Tests
Browne, C.; Tavener, S.
Page(s): 112 - 119
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6185647
5. Information Set Monte Carlo Tree Search
Cowling, P.I.; Powley, E.J.; Whitehouse, D.
Page(s): 120 - 143
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203567
6. Benchmarks for Grid-Based Pathfinding
Sturtevant, N.R.
Page(s): 144 - 148
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6194296
Friday, August 3, 2012
IEEE Transactions on Evolutionary Computation: Volume 16, Issue 4, 2012
1. Solving Multicommodity Capacitated Network Design Problems Using Multiobjective Evolutionary Algorithms
Kleeman, M. P.; Seibert, B. A.; Lamont, G. B.; Hopkinson, K. M.; Graham, S. R.
Page(s): 449 - 471
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151105
2. An Integrated Neuroevolutionary Approach to Reactive Control and High-Level Strategy
Kohl, N.; Miikkulainen, R.
Page(s): 472 - 488
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151106
3. A Process Algebra Genetic Algorithm
Karaman, S.; Shima, T.; Frazzoli, E.
Page(s): 489 - 503
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6045330
4. Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization
Schutze, O.; Esquivel, X.; Lara, A.; Coello, C. A. C.
Page(s): 504 - 522
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151115
5. Promoting Creative Design in Interactive Evolutionary Computation
Kowaliw, T.; Dorin, A.; McCormack, J.
Page(s): 523 - 536
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151108
6. Effects of Iterated Interactions in Multiplayer Spatial Evolutionary Games
Chiong, R.; Kirley, M.
Page(s): 537 - 555
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151098
7. A General Framework of Multipopulation Methods With Clustering in Undetectable Dynamic Environments
Li, C.; Yang, S.
Page(s): 556 - 577
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151109
8. On the Design of Constraint Covariance Matrix Self-Adaptation Evolution Strategies Including a Cardinality Constraint
Beyer, H.-G.; Finck, S.
Page(s): 578 - 596
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151095
Kleeman, M. P.; Seibert, B. A.; Lamont, G. B.; Hopkinson, K. M.; Graham, S. R.
Page(s): 449 - 471
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151105
2. An Integrated Neuroevolutionary Approach to Reactive Control and High-Level Strategy
Kohl, N.; Miikkulainen, R.
Page(s): 472 - 488
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151106
3. A Process Algebra Genetic Algorithm
Karaman, S.; Shima, T.; Frazzoli, E.
Page(s): 489 - 503
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6045330
4. Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization
Schutze, O.; Esquivel, X.; Lara, A.; Coello, C. A. C.
Page(s): 504 - 522
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151115
5. Promoting Creative Design in Interactive Evolutionary Computation
Kowaliw, T.; Dorin, A.; McCormack, J.
Page(s): 523 - 536
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151108
6. Effects of Iterated Interactions in Multiplayer Spatial Evolutionary Games
Chiong, R.; Kirley, M.
Page(s): 537 - 555
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151098
7. A General Framework of Multipopulation Methods With Clustering in Undetectable Dynamic Environments
Li, C.; Yang, S.
Page(s): 556 - 577
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151109
8. On the Design of Constraint Covariance Matrix Self-Adaptation Evolution Strategies Including a Cardinality Constraint
Beyer, H.-G.; Finck, S.
Page(s): 578 - 596
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151095
Thursday, August 2, 2012
IEEE Transactions on Fuzzy Systems: Volume 20, Issue 4, 2012
1. Finite-Time $H_{infty}$ Fuzzy Control of Nonlinear Jump Systems With Time Delays Via Dynamic Observer-Based State Feedback
He, S.; Liu, F.
Page(s): 605 - 614
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6094200
2. A Practical Approach to R&D Portfolio Selection Using the Fuzzy Pay-Off Method
Hassanzadeh, F.; Collan, M.; Modarres, M.
Page(s): 615 - 622
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6109284
3. Fuzzy Hardware: A Retrospective and Analysis
Zavala, A. H.; Nieto, O. C.
Page(s): 623 - 635
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6111466
4. On Robust Fuzzy Rough Set Models
Hu, Q.; Zhang, L.; An, S.; Zhang, D.; Yu, D.
Page(s): 636 - 651
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6111464
5. Fault-Tolerant Control for T–S Fuzzy Systems With Application to Near-Space Hypersonic Vehicle With Actuator Faults
Shen, Q.; Jiang, B.; Cocquempot, V.
Page(s): 652 - 665
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6111465
6. Constrained Fuzzy Hierarchical Analysis for Portfolio Selection Under Higher Moments
Nguyen, T. T.; Gordon-Brown, L.
Page(s): 666 - 682
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6112209
7. An Integrated Mechanism for Feature Selection and Fuzzy Rule Extraction for Classification
Chen, Y-.C.; Pal, N. R.; Chung, I-.F.
Page(s): 683 - 698
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6112676
8. Generalizing the Decentralized Control of Fuzzy Discrete Event Systems
Jayasiri, A.; Mann, G. K. I.; Gosine, R. G.
Page(s): 699 - 714
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6112712
9. Participatory Learning of Propositional Knowledge
Yager, R. R.
Page(s): 715 - 727
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6119214
10. The $K$-Means-Type Algorithms Versus Imbalanced Data Distributions
Liang, J.; Bai, L.; Dang, C.; Cao, F.
Page(s): 728 - 745
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6121900
11. Stress Monitoring Based on Stochastic Fuzzy Analysis of Heartbeat Intervals
Kumar, M.; Neubert, S.; Behrendt, S.; Rieger, A.; Weippert, M.; Stoll, N.; Thurow, K.; Stoll, R.
Page(s): 746 - 759
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6127913
12. Fuzzy Preferences in the Graph Model for Conflict Resolution
Bashar, M. A.; Kilgour, D. M.; Hipel, K. W.
Page(s): 760 - 770
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6127912
13. Observer-Based Adaptive Fuzzy Backstepping Output Feedback Control of Uncertain MIMO Pure-Feedback Nonlinear Systems
Tong, S. C.; Li, Y. M.; Shi, P.
Page(s): 771 - 785
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6126023
14. On the Use of a Fuzzy Object-Relational Database for Flexible Retrieval of Medical Images
Medina, J. M.; Jaime-Castillo, S.; Barranco, C. D.; Campana, J. R.
Page(s): 786 - 803
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208854
He, S.; Liu, F.
Page(s): 605 - 614
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6094200
2. A Practical Approach to R&D Portfolio Selection Using the Fuzzy Pay-Off Method
Hassanzadeh, F.; Collan, M.; Modarres, M.
Page(s): 615 - 622
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6109284
3. Fuzzy Hardware: A Retrospective and Analysis
Zavala, A. H.; Nieto, O. C.
Page(s): 623 - 635
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6111466
4. On Robust Fuzzy Rough Set Models
Hu, Q.; Zhang, L.; An, S.; Zhang, D.; Yu, D.
Page(s): 636 - 651
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6111464
5. Fault-Tolerant Control for T–S Fuzzy Systems With Application to Near-Space Hypersonic Vehicle With Actuator Faults
Shen, Q.; Jiang, B.; Cocquempot, V.
Page(s): 652 - 665
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6111465
6. Constrained Fuzzy Hierarchical Analysis for Portfolio Selection Under Higher Moments
Nguyen, T. T.; Gordon-Brown, L.
Page(s): 666 - 682
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6112209
7. An Integrated Mechanism for Feature Selection and Fuzzy Rule Extraction for Classification
Chen, Y-.C.; Pal, N. R.; Chung, I-.F.
Page(s): 683 - 698
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6112676
8. Generalizing the Decentralized Control of Fuzzy Discrete Event Systems
Jayasiri, A.; Mann, G. K. I.; Gosine, R. G.
Page(s): 699 - 714
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6112712
9. Participatory Learning of Propositional Knowledge
Yager, R. R.
Page(s): 715 - 727
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6119214
10. The $K$-Means-Type Algorithms Versus Imbalanced Data Distributions
Liang, J.; Bai, L.; Dang, C.; Cao, F.
Page(s): 728 - 745
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6121900
11. Stress Monitoring Based on Stochastic Fuzzy Analysis of Heartbeat Intervals
Kumar, M.; Neubert, S.; Behrendt, S.; Rieger, A.; Weippert, M.; Stoll, N.; Thurow, K.; Stoll, R.
Page(s): 746 - 759
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6127913
12. Fuzzy Preferences in the Graph Model for Conflict Resolution
Bashar, M. A.; Kilgour, D. M.; Hipel, K. W.
Page(s): 760 - 770
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6127912
13. Observer-Based Adaptive Fuzzy Backstepping Output Feedback Control of Uncertain MIMO Pure-Feedback Nonlinear Systems
Tong, S. C.; Li, Y. M.; Shi, P.
Page(s): 771 - 785
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6126023
14. On the Use of a Fuzzy Object-Relational Database for Flexible Retrieval of Medical Images
Medina, J. M.; Jaime-Castillo, S.; Barranco, C. D.; Campana, J. R.
Page(s): 786 - 803
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208854
Wednesday, August 1, 2012
Reminder: paper submission deadline for AROB 2013
A reminder that the deadline for submitting papers to the 18th International Symposium on Artificial Life and Robotics (AROB) 2013 is 1 September, 2012. This symposium will be held in Daejeon, Korea, January 30 - February 1st, 2013.
Monday, July 30, 2012
IEEE Transactions on Neural Networks and Learning Systems; Volume 23, Issue 8, August 2012
1. Title: Twenty Years of Mixture of Experts
Authors: Seniha Esen Yuksel; Joseph N. Wilson; Paul D. Gader
Page(s): 1177 - 1193
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6215056
2. Title: Constrained Empirical Risk Minimization Framework for Distance Metric Learning
Authors: Wei Bian; Dacheng Tao
Page(s): 1194 - 1205
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203595
3. Title: Scale-Invariant Amplitude Spectrum Modulation for Visual Saliency Detection
Authors: Dongyue Chen; Hao Chu
Page(s): 1206 - 1214
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6212362
4. Title: Relaxed Fault-Tolerant Hardware Implementation of Neural Networks in the Presence of Multiple Transient Errors
Authors: Hamid Reza Mahdiani; Sied Mehdi Fakhraie; Caro Lucas
Page(s): 1215 - 1228
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6213557
5. Title: Mapping Dynamic Bayesian Networks to $alpha$-Shapes: Application to Human Faces Identification Across Ages
Authors: Djamel Bouchaffra
Page(s): 1229 - 1241
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6215055
6. Title: Predictive Approach for User Long-Term Needs in Content-Based Image Suggestion
Authors: Sabri Boutemedjet; Djemel Ziou
Page(s): 1242 - 1253
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6218198
7. Title: SOMKE: Kernel Density Estimation Over Data Streams by Sequences of Self-Organizing Maps
Authors: Yuan Cao; Haibo He; Hong Man
Page(s): 1254 - 1268
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6218200
8. Title: Reinforced Two-Step-Ahead Weight Adjustment Technique for Online Training of Recurrent Neural Networks
Authors: Li-Chiu Chang; Pin-An Chen; Fi-John Chang
Page(s): 1269 - 1278
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6218199
9. Title: Spatial Gaussian Process Regression With Mobile Sensor Networks
Authors: Dongbing Gu; Huosheng Hu
Page(s): 1279 - 1290
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6218781
10. Title: Adaptive Data Embedding Framework for Multiclass Classification
Authors: Tingting Mu; Jianmin Jiang; Yan Wang; John Y. Goulermas
Page(s): 1291 - 1303
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6220302
11. Title: Study on the Impact of Partition-Induced Dataset Shift on $k$-Fold Cross-Validation
Authors: Jose García Moreno-Torres; José A. Sáez; Francisco Herrera
Page(s): 1304 - 1312
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6226477
12. Title: Kernel Recursive Least-Squares Tracker for Time-Varying Regression
Authors: Steven Van Vaerenbergh; Miguel Lázaro-Gredilla; Ignacio Santamaría
Page(s): 1313 - 1326
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6227361
13. Title: Discrete-Time Neural Inverse Optimal Control for Nonlinear Systems via Passivation
Authors: Fernando Ornelas-Tellez; Edgar N. Sanchez; Alexander G. Loukianov
Page(s): 1327 - 1339
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6238379
14. Title: Equilibria of Perceptrons for Simple Contingency Problems
Authors: Michael R. W. Dawson; Brian Dupuis
Page(s): 1340- 1344
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6213123
Authors: Seniha Esen Yuksel; Joseph N. Wilson; Paul D. Gader
Page(s): 1177 - 1193
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6215056
2. Title: Constrained Empirical Risk Minimization Framework for Distance Metric Learning
Authors: Wei Bian; Dacheng Tao
Page(s): 1194 - 1205
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203595
3. Title: Scale-Invariant Amplitude Spectrum Modulation for Visual Saliency Detection
Authors: Dongyue Chen; Hao Chu
Page(s): 1206 - 1214
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6212362
4. Title: Relaxed Fault-Tolerant Hardware Implementation of Neural Networks in the Presence of Multiple Transient Errors
Authors: Hamid Reza Mahdiani; Sied Mehdi Fakhraie; Caro Lucas
Page(s): 1215 - 1228
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6213557
5. Title: Mapping Dynamic Bayesian Networks to $alpha$-Shapes: Application to Human Faces Identification Across Ages
Authors: Djamel Bouchaffra
Page(s): 1229 - 1241
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6215055
6. Title: Predictive Approach for User Long-Term Needs in Content-Based Image Suggestion
Authors: Sabri Boutemedjet; Djemel Ziou
Page(s): 1242 - 1253
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6218198
7. Title: SOMKE: Kernel Density Estimation Over Data Streams by Sequences of Self-Organizing Maps
Authors: Yuan Cao; Haibo He; Hong Man
Page(s): 1254 - 1268
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6218200
8. Title: Reinforced Two-Step-Ahead Weight Adjustment Technique for Online Training of Recurrent Neural Networks
Authors: Li-Chiu Chang; Pin-An Chen; Fi-John Chang
Page(s): 1269 - 1278
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6218199
9. Title: Spatial Gaussian Process Regression With Mobile Sensor Networks
Authors: Dongbing Gu; Huosheng Hu
Page(s): 1279 - 1290
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6218781
10. Title: Adaptive Data Embedding Framework for Multiclass Classification
Authors: Tingting Mu; Jianmin Jiang; Yan Wang; John Y. Goulermas
Page(s): 1291 - 1303
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6220302
11. Title: Study on the Impact of Partition-Induced Dataset Shift on $k$-Fold Cross-Validation
Authors: Jose García Moreno-Torres; José A. Sáez; Francisco Herrera
Page(s): 1304 - 1312
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6226477
12. Title: Kernel Recursive Least-Squares Tracker for Time-Varying Regression
Authors: Steven Van Vaerenbergh; Miguel Lázaro-Gredilla; Ignacio Santamaría
Page(s): 1313 - 1326
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6227361
13. Title: Discrete-Time Neural Inverse Optimal Control for Nonlinear Systems via Passivation
Authors: Fernando Ornelas-Tellez; Edgar N. Sanchez; Alexander G. Loukianov
Page(s): 1327 - 1339
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6238379
14. Title: Equilibria of Perceptrons for Simple Contingency Problems
Authors: Michael R. W. Dawson; Brian Dupuis
Page(s): 1340- 1344
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6213123
Friday, July 27, 2012
Fraud in science
Ars Technica has a slightly tongue-in-cheek article on how to commit scientific fraud and get away with it. The article discusses eight points:
A long list of co-authors is not as common in CI (point 2) as it is in other fields, but I have seen many, many papers that are going over the same topic as has been covered many times before (point 3). Also, many, many papers cover minimal, slightly incremental "improvements" to existing algorithms that are of little true interest to most other researchers (point 4).
While one of the great joys of working in computational intelligence lies in the broad range of applications the field can be applied to, it does provide more opportunity to publish in journals that specialise is other fields (point 5).
The remaining three points (6-8) are more concerned with how not to get caught, or rather, how not to draw attention to yourself while committing fraud.
Fraud is always a problem, and I don't think that it is any less common in CI than in any other field. A greater emphasis on the use of statistics in CI papers would help guard against fraud (see my posts here and here about increasing the statistical basis of CI papers). But apart from that, we still depend on the honesty and integrity of the authors.
- Fake data nobody ever expects to see
- Work with many collaborators
- Tell people what they already know
- Don't do research anyone cares about
- Don't publish in journals focused on your field
- Distribute responsibility
- Don't plagiarize
- Don't duplicate images
A long list of co-authors is not as common in CI (point 2) as it is in other fields, but I have seen many, many papers that are going over the same topic as has been covered many times before (point 3). Also, many, many papers cover minimal, slightly incremental "improvements" to existing algorithms that are of little true interest to most other researchers (point 4).
While one of the great joys of working in computational intelligence lies in the broad range of applications the field can be applied to, it does provide more opportunity to publish in journals that specialise is other fields (point 5).
The remaining three points (6-8) are more concerned with how not to get caught, or rather, how not to draw attention to yourself while committing fraud.
Fraud is always a problem, and I don't think that it is any less common in CI than in any other field. A greater emphasis on the use of statistics in CI papers would help guard against fraud (see my posts here and here about increasing the statistical basis of CI papers). But apart from that, we still depend on the honesty and integrity of the authors.
Thursday, July 26, 2012
Reminder: IEEE CIS Facebook Photo Competition
The IEEE Computational Intelligence Society are running a photo
competition on Facebook. See the flyer below to find out how to enter.
Wednesday, July 25, 2012
More on open access journals
Continuing my series of posts on open access journals (see here and here), this article by Simon Owens in U.S. News is an excellent and detailed review of the debate. The article compares open access journals to e-books: while e-books have existed for a long time, it is only in the last five years that they have really taken off, after reaching a tipping point. Owens argues that open access journals have reached that tipping point, and the academic journal publishing business (known for the huge profits they extract from university libraries) is on the verge of serious disruption.
I tend to agree with his assessment, open access journals have been flying largely under the radar for a long time, but I get the sense that they are becoming more accepted among the top researchers: when more top researchers publish in open-access journals, they will gain credibility.
The old publishing model is being destroyed by greed: journals are just too expensive, and suck too much money out of universities that should be spent funding research and paying people's salaries. Open access is the future of scientific publishing.
I tend to agree with his assessment, open access journals have been flying largely under the radar for a long time, but I get the sense that they are becoming more accepted among the top researchers: when more top researchers publish in open-access journals, they will gain credibility.
The old publishing model is being destroyed by greed: journals are just too expensive, and suck too much money out of universities that should be spent funding research and paying people's salaries. Open access is the future of scientific publishing.
Tuesday, July 24, 2012
A small victory for open access 2
Following up from my earlier post, this article in The Economist gives a pretty good overview of the recent UK and EU move towards requiring the outputs of publicly-funded research being published as open access. The article also gives a lot of context about the different open access publishing models - the "gold" model practiced by PLoS, where authors pay a fee to publish; and the "green" model that the USA's NIH demands, whereby papers are published in traditional journals, but the journals must allow authors to publish their papers in an open repository like PubMed after one year.
So, when are we going to start seeing one of these models applied to computational intelligence journals? I'd be especially pleased if the IEEE were to adopt one of these models, as they lock every single paper they publish up behind a paywall, seemingly for all of time.
So, when are we going to start seeing one of these models applied to computational intelligence journals? I'd be especially pleased if the IEEE were to adopt one of these models, as they lock every single paper they publish up behind a paywall, seemingly for all of time.
Monday, July 23, 2012
Conference paper deadline: KES-IDT 2013
The deadline for submitting papers to the 5th International Conference on Intelligent Decision Technologies (KES-IDT) is 6 January 2013. This conference will be held in Sesimbra, Portugal, 26-28 June 2013.
Friday, July 20, 2012
A small victory for open access
All taxpayer-funded research in the UK must now be published as open access papers, according to this article in the BBC. The British government will be providing £50m in subsidies for researchers to pay the fees necessary to have their work available as open access.
This is a victory for open access. But, the victory is not complete. Firstly, the £50m is coming out of general research funding, it's not new money. In other words, there will be less research done because of this, as there will be less money available to fund it. Secondly, the money is going to the established academic publishers, who are just going to use it to further pad their profits. Finally, as the article states, many journals will still not accept articles that have the relevant data available from open data repositories.
I still think that eventually, open access journals will over-whelm the old publishers. But they can only do this if the top researchers contribute quality research articles to them. Meanwhile, I personally think that the next step is for reviewers (and editors) to start demanding payment for the labour they provide to the publishers. It is we reviewers and editors who provide the quality control for the journals, it's time we got paid for it.
Would anyone be willing to sign up for a boycott of all publishers, until reviewers and editors are paid?
This is a victory for open access. But, the victory is not complete. Firstly, the £50m is coming out of general research funding, it's not new money. In other words, there will be less research done because of this, as there will be less money available to fund it. Secondly, the money is going to the established academic publishers, who are just going to use it to further pad their profits. Finally, as the article states, many journals will still not accept articles that have the relevant data available from open data repositories.
I still think that eventually, open access journals will over-whelm the old publishers. But they can only do this if the top researchers contribute quality research articles to them. Meanwhile, I personally think that the next step is for reviewers (and editors) to start demanding payment for the labour they provide to the publishers. It is we reviewers and editors who provide the quality control for the journals, it's time we got paid for it.
Would anyone be willing to sign up for a boycott of all publishers, until reviewers and editors are paid?
IEEE Transactions on Fuzzy Systems, Volume 20, Issue 3, 2012
IEEE Transactions on Fuzzy Systems, Volume 20, Issue 3, 2012
1. Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons
Bustince, H.; Pagola, M.; Mesiar, R.; Hullermeier, E.; Herrera, F.
Page(s): 405 - 415
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6060906
2. Analytical Structure and Characteristics of Symmetric Karnik–Mendel Type-Reduced Interval Type-2 Fuzzy PI and PD Controllers
Maowen Nie; Woei Wan Tan
Page(s): 416 - 430
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6064887
3. Delay-Dependent Decentralized H_\infty Filtering for Discrete-Time Nonlinear Interconnected Systems With Time-Varying Delay Based on the T–S Fuzzy Model
Hongbin Zhang; Hua Zhong; Chuangyin Dang
Page(s): 431 - 443
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6072261
4. Collaborative Fuzzy Clustering Algorithms: Some Refinements and Design Guidelines
Coletta, L.F.S.; Vendramin, L.; Hruschka, E.R.; Campello, R.J.G.B.; Pedrycz, W.
Page(s): 444 - 462
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6074934
5. Fuzzy Wavelet Neural Network With an Accelerated Hybrid Learning Algorithm
Davanipoor, M.; Zekri, M.; Sheikholeslam, F.
Page(s): 463 - 470
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6081924
6. Adaptive Control Schemes for Discrete-Time T–S Fuzzy Systems With Unknown Parameters and Actuator Failures
Ruiyun Qi; Gang Tao; Bin Jiang; Chang Tan
Page(s): 471 - 486
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6084736
7. Aggregation for Atanassov’s Intuitionistic and Interval Valued Fuzzy Sets: The Median Operator
Beliakov, G.; Bustince, H.; James, S.; Calvo, T.; Fernandez, J.
Page(s): 487 - 498
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6086758
8. Enhanced Interval Approach for Encoding Words Into Interval Type-2 Fuzzy Sets and Its Convergence Analysis
Dongrui Wu; Mendel, J.M.; Coupland, S.
Page(s): 499 - 513
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6086759
9. Intuitionistic Fuzzy Multiattribute Decision Making: An Interactive Method
Zeshui Xu
Page(s): 514 - 525
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6087279
10. Entailment Principle for Measure-Based Uncertainty
Yager, R.R.
Page(s): 526 - 535
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6094201
11. Learning Error Feedback Design of Direct Adaptive Fuzzy Control Systems
Yao-Chu Hsueh; Shun-Feng Su
Page(s): 536 - 545
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6097053
12. Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures
Hullermeier, E.; Rifqi, M.; Henzgen, S.; Senge, R.
Page(s): 546 - 556
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6104134
13. A Generalization of Distance Functions for Fuzzy c -Means Clustering With Centroids of Arithmetic Means
Junjie Wu; Hui Xiong; Chen Liu; Jian Chen
Page(s): 557 - 571
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6104135
14. Decentralized Fault-Tolerant Control for Satellite Attitude Synchronization
Junquan Li; Kumar, K.D.
Page(s): 572 - 586
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6108359
15. Fuzzy Adaptive Tracking Control of Wheeled Mobile Robots With State-Dependent Kinematic and Dynamic Disturbances
Dongkyoung Chwa
Page(s): 587 - 593
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6084735
16. Nonquadratic Stabilization of Continuous T–S Fuzzy Models: LMI Solution for a Local Approach
Jun-Tao Pan; Guerra, T.M.; Shu-Min Fei; Jaadari, A.
Page(s): 594 - 602
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6104133
1. Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons
Bustince, H.; Pagola, M.; Mesiar, R.; Hullermeier, E.; Herrera, F.
Page(s): 405 - 415
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6060906
2. Analytical Structure and Characteristics of Symmetric Karnik–Mendel Type-Reduced Interval Type-2 Fuzzy PI and PD Controllers
Maowen Nie; Woei Wan Tan
Page(s): 416 - 430
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6064887
3. Delay-Dependent Decentralized H_\infty Filtering for Discrete-Time Nonlinear Interconnected Systems With Time-Varying Delay Based on the T–S Fuzzy Model
Hongbin Zhang; Hua Zhong; Chuangyin Dang
Page(s): 431 - 443
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6072261
4. Collaborative Fuzzy Clustering Algorithms: Some Refinements and Design Guidelines
Coletta, L.F.S.; Vendramin, L.; Hruschka, E.R.; Campello, R.J.G.B.; Pedrycz, W.
Page(s): 444 - 462
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6074934
5. Fuzzy Wavelet Neural Network With an Accelerated Hybrid Learning Algorithm
Davanipoor, M.; Zekri, M.; Sheikholeslam, F.
Page(s): 463 - 470
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6081924
6. Adaptive Control Schemes for Discrete-Time T–S Fuzzy Systems With Unknown Parameters and Actuator Failures
Ruiyun Qi; Gang Tao; Bin Jiang; Chang Tan
Page(s): 471 - 486
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6084736
7. Aggregation for Atanassov’s Intuitionistic and Interval Valued Fuzzy Sets: The Median Operator
Beliakov, G.; Bustince, H.; James, S.; Calvo, T.; Fernandez, J.
Page(s): 487 - 498
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6086758
8. Enhanced Interval Approach for Encoding Words Into Interval Type-2 Fuzzy Sets and Its Convergence Analysis
Dongrui Wu; Mendel, J.M.; Coupland, S.
Page(s): 499 - 513
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6086759
9. Intuitionistic Fuzzy Multiattribute Decision Making: An Interactive Method
Zeshui Xu
Page(s): 514 - 525
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6087279
10. Entailment Principle for Measure-Based Uncertainty
Yager, R.R.
Page(s): 526 - 535
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6094201
11. Learning Error Feedback Design of Direct Adaptive Fuzzy Control Systems
Yao-Chu Hsueh; Shun-Feng Su
Page(s): 536 - 545
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6097053
12. Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures
Hullermeier, E.; Rifqi, M.; Henzgen, S.; Senge, R.
Page(s): 546 - 556
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6104134
13. A Generalization of Distance Functions for Fuzzy c -Means Clustering With Centroids of Arithmetic Means
Junjie Wu; Hui Xiong; Chen Liu; Jian Chen
Page(s): 557 - 571
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6104135
14. Decentralized Fault-Tolerant Control for Satellite Attitude Synchronization
Junquan Li; Kumar, K.D.
Page(s): 572 - 586
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6108359
15. Fuzzy Adaptive Tracking Control of Wheeled Mobile Robots With State-Dependent Kinematic and Dynamic Disturbances
Dongkyoung Chwa
Page(s): 587 - 593
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6084735
16. Nonquadratic Stabilization of Continuous T–S Fuzzy Models: LMI Solution for a Local Approach
Jun-Tao Pan; Guerra, T.M.; Shu-Min Fei; Jaadari, A.
Page(s): 594 - 602
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6104133
Thursday, July 19, 2012
Reminder: paper submission deadline for EMO 2013
A reminder that the deadline for submitting papers to the 7th International Conference on Evolutionary Multi-Criterion Optimization (EMO) 2013 is 19 August 2012. This conference will be held in Sheffield, UK, 19-22 March, 2013.
Wednesday, July 18, 2012
IEEE Transactions on Evolutionary Computation: Volume 16, Issue 3, 2012
Table of contents for IEEE Transactions on Evolutionary Computation Volume 16, Issue 3, 2012.
1. A Cluster and Gradient-Based Artificial Immune System Applied in Optimization Scenarios
de Mello Honorio, L.; da Silva, A.M.L.; Barbosa, D.A.
Page(s): 301 - 318
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6204227
2. Maximum Satisfiability: Anatomy of the Fitness Landscape for a Hard Combinatorial Optimization Problem
Prugel-Bennett, A.; Tayarani-Najaran, M.-H.
Page(s): 319 - 338
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6045332
3. Real-Coded Chemical Reaction Optimization
Lam, A.Y.S.; Li, V.O.K.; Yu, J.J.Q.
Page(s): 339 - 353
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6029981
4. A Study of Collapse in Bare Bones Particle Swarm Optimization
Blackwell, T.
Page(s): 354 - 372
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6029979
5. Multiobjectivization via Helper-Objectives With the Tunable Objectives Problem
Lochtefeld, D.F.; Ciarallo, F.W.
Page(s): 373 - 390
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6029982
6. Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System
Dupuis, J.; Zhun Fan; Goodman, E.D.
Page(s): 391 - 405
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6045329
7. Grammatical Evolution of Local Search Heuristics
Burke, E.K.; Hyde, M.R.; Kendall, G.
Page(s): 406 - 417
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6029980
8. A Multiobjective Genetic Algorithm to Find Communities in Complex Networks
Pizzuti, C.
Page(s): 418 - 430
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6045331
9. A Genetic Approach to Statistical Disclosure Control
Smith, J.E.; Clark, A.R.; Staggemeier, A.T.; Serpell, M.C.
Page(s): 431 - 441
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6036172
10. Decomposition-Based Multiobjective Evolutionary Algorithm With an Ensemble of Neighborhood Sizes
Shi-Zheng Zhao; Suganthan, P.N.; Qingfu Zhang
Page(s): 442 - 446
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151117
Tuesday, July 17, 2012
Call for papers: WCCI 2014
While WCCI 2012 has only just ended, preparations for the World Congress on Computational Intelligence (WCCI) 2014 have already begun. WCCI 2014 will consist of the International Joint Conference on Neural Networks (IJCNN), the International Conference on Fuzzy Systems (FUZZ-IEEE) and the Congress on Evolutionary Computations (CEC). This congress will be held in Beijing, China, July 6-11, 2014.
The deadline for submitting papers to each of these three conferences is December 20, 2013.
The deadline for submitting papers to each of these three conferences is December 20, 2013.
Monday, July 16, 2012
Conference paper deadline: ICAISC 2013
The deadline for submitting papers to the International Conference on Artificial Intelligence and Soft Computing (ICAISC) 2013 is November 20, 2012. This conference will be held in Zakopane, Poland, June 9-13, 2013.
Wednesday, July 11, 2012
IEEE Transactions on Neural Networks and Learning Systems; Volume 23, Issue 7, July 2012
1. Title: L1/2 Regularization: A Thresholding Representation Theory and a Fast Solver
Authors: Zongben Xu; Xiangyu Chang; Fengmin Xu; Hai Zhang
Page(s): 1013 - 1027
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6205396
2. Title: Toward Automatic Time-Series Forecasting Using Neural Networks
Authors: Weizhong Yan
Page(s): 1028 - 1039
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6210391
3.Title: Novel Cascade FPGA Accelerator for Support Vector Machines Classification
Authors: Markos Papadonikolakis; Christos-Savvas Bouganis
Page(s): 1040 - 1052
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6197724
4. Title: Robust GRBF Static Neurocontroller With Switch Logic for Control of Robot Manipulators
Authors: Juan Ignacio Mulero-Martínez
Page(s): 1053 - 1064
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6198898
5. Title: VLSI Implementation of a Bio-Inspired Olfactory Spiking Neural Network
Authors: Hung-Yi Hsieh; Kea-Tiong Tang
Page(s): 1065 - 1073
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6202348
6. Title: Transductive Ordinal Regression
Authors: Chun-Wei Seah; Ivor W. Tsang; Yew-Soon Ong
Page(s): 1074 - 1086
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203451
7. Title: Online Nonnegative Matrix Factorization With Robust Stochastic Approximation
Authors: Naiyang Guan; Dacheng Tao; Zhigang Luo; Bo Yuan
Page(s): 1087 - 1099
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203594
8. Title: SSC: A Classifier Combination Method Based on Signal Strength
Authors: Haibo He; Yuan Cao
Page(s): 1100 - 1117
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6204134
9. Title: Online Optimal Control of Affine Nonlinear Discrete-Time Systems With Unknown Internal Dynamics by Using Time-Based Policy Update
Authors: Travis Dierks; Sarangapani Jagannathan
Page(s): 1118 - 1129
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208889
10. Title: Reproducing Kernel Hilbert Space Approach for the Online Update of Radial Bases in Neuro-Adaptive Control
Authors: Hassan A. Kingravi; Girish Chowdhary; Patricio A. Vela; Eric N. Johnson
Page(s): 1130 - 1141
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208915
11. Title: Simple Proof of Convergence of the SMO Algorithm for Different SVM Variants
Authors: Jorge López; José R. Dorronsoro
Page(s): 1142 - 1147
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6193217
12. Title: RBF Networks Under the Concurrent Fault Situation
Authors: Chi-Sing Leung; John Pui-Fai Sum
Page(s): 1148 - 1155
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203419
13. Title: Neural Network-Based Distributed Attitude Coordination Control for Spacecraft Formation Flying With Input Saturation
Authors: An-Min Zou; Krishna Dev Kumar
Page(s): 1155 - 1162
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203597
14. Title: Universal Neural Network Control of MIMO Uncertain Nonlinear Systems
Authors: Qinmin Yang; Zaiyue Yang; Youxian Sun
Page(s): 1163 - 1169
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203596
15. Title: Spectral Graph Optimization for Instance Reduction
Authors: Konstantinos Nikolaidis; Eduardo Rodriguez-Martinez; John Yannis Goulermas; Q. H. Wu
Page(s): 1169 - 1175
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208890
Authors: Zongben Xu; Xiangyu Chang; Fengmin Xu; Hai Zhang
Page(s): 1013 - 1027
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6205396
2. Title: Toward Automatic Time-Series Forecasting Using Neural Networks
Authors: Weizhong Yan
Page(s): 1028 - 1039
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6210391
3.Title: Novel Cascade FPGA Accelerator for Support Vector Machines Classification
Authors: Markos Papadonikolakis; Christos-Savvas Bouganis
Page(s): 1040 - 1052
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6197724
4. Title: Robust GRBF Static Neurocontroller With Switch Logic for Control of Robot Manipulators
Authors: Juan Ignacio Mulero-Martínez
Page(s): 1053 - 1064
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6198898
5. Title: VLSI Implementation of a Bio-Inspired Olfactory Spiking Neural Network
Authors: Hung-Yi Hsieh; Kea-Tiong Tang
Page(s): 1065 - 1073
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6202348
6. Title: Transductive Ordinal Regression
Authors: Chun-Wei Seah; Ivor W. Tsang; Yew-Soon Ong
Page(s): 1074 - 1086
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203451
7. Title: Online Nonnegative Matrix Factorization With Robust Stochastic Approximation
Authors: Naiyang Guan; Dacheng Tao; Zhigang Luo; Bo Yuan
Page(s): 1087 - 1099
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203594
8. Title: SSC: A Classifier Combination Method Based on Signal Strength
Authors: Haibo He; Yuan Cao
Page(s): 1100 - 1117
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6204134
9. Title: Online Optimal Control of Affine Nonlinear Discrete-Time Systems With Unknown Internal Dynamics by Using Time-Based Policy Update
Authors: Travis Dierks; Sarangapani Jagannathan
Page(s): 1118 - 1129
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208889
10. Title: Reproducing Kernel Hilbert Space Approach for the Online Update of Radial Bases in Neuro-Adaptive Control
Authors: Hassan A. Kingravi; Girish Chowdhary; Patricio A. Vela; Eric N. Johnson
Page(s): 1130 - 1141
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208915
11. Title: Simple Proof of Convergence of the SMO Algorithm for Different SVM Variants
Authors: Jorge López; José R. Dorronsoro
Page(s): 1142 - 1147
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6193217
12. Title: RBF Networks Under the Concurrent Fault Situation
Authors: Chi-Sing Leung; John Pui-Fai Sum
Page(s): 1148 - 1155
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203419
13. Title: Neural Network-Based Distributed Attitude Coordination Control for Spacecraft Formation Flying With Input Saturation
Authors: An-Min Zou; Krishna Dev Kumar
Page(s): 1155 - 1162
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203597
14. Title: Universal Neural Network Control of MIMO Uncertain Nonlinear Systems
Authors: Qinmin Yang; Zaiyue Yang; Youxian Sun
Page(s): 1163 - 1169
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6203596
15. Title: Spectral Graph Optimization for Instance Reduction
Authors: Konstantinos Nikolaidis; Eduardo Rodriguez-Martinez; John Yannis Goulermas; Q. H. Wu
Page(s): 1169 - 1175
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6208890
Tuesday, July 10, 2012
Reminder: paper submission deadline for IEEE-SSCI 2013
A reminder that the deadline for the IEEE Symposium Series in Computational Intelligence 2013 is 10 October 2012. This series of symposia will be held in Singapore 16-19 April 2013.
Thursday, July 5, 2012
Reminder: paper submission deadline for Fuzz-IEEE 2013
A reminder that the deadline for submitting papers to the IEEE Conference on Fuzzy Systems (Fuzz-IEEE) 2013 is 5 January, 2013. This conference will be held in Hyderabad, India, 7-10 July, 2013.
Wednesday, July 4, 2012
Reminder: IEEE CIS Facebook Photo Competition
The IEEE Computational Intelligence Society are running a photo
competition on Facebook. See the flyer below to find out how to enter.
Friday, June 29, 2012
Google Brain
The so-called Google Brain has been in the news the last couple of days (see for example here, here and here, and see here for coverage from the ABC, including part of an interview I did with them on the subject).
The news coverage has focussed on how the machine learned to recognise cats, because cats are cute. Reading the original paper gives a more nuanced view of the technology. The researchers constructed a colossal neural network with one billion neurons, implemented over 1000 16-processor servers. They then presented it with ten million images taken from YouTube, and left it to train for three days before looking to see what it had learned.
The researchers knew that the three most common images on YouTube were cats, human faces, and human bodies. So, they presented images drawn from independent data sets (that is, data sets that were not involved in training the network) that were known to be of cats, faces or bodies, and saw which parts of the network activated. By examining the activations within the network, they found that there were prototypes of cats, faces and bodies within the network. That is, they showed that the network had formed its own exemplars of these objects.
There are four main technical innovations in this paper:
1) The size of the network, which had one billion artificial neurons.
2) The technique they used to reduce the interconnections between the elements of the network, to make it easier to execute in parallel across the 16 000 processors they used.
3) The number of images (ten million) used to train the network.
4) The size of the images used (200 x 200 pixels, which is larger than most).
The network did not learn to recognise cats, faces, or bodies. It still doesn't know what a cat is, or what a face is, or what a human body is. It has no concept of what the images represent. But even so, it still has potential: neural networks have finally reached the age of Big Data.
The news coverage has focussed on how the machine learned to recognise cats, because cats are cute. Reading the original paper gives a more nuanced view of the technology. The researchers constructed a colossal neural network with one billion neurons, implemented over 1000 16-processor servers. They then presented it with ten million images taken from YouTube, and left it to train for three days before looking to see what it had learned.
The researchers knew that the three most common images on YouTube were cats, human faces, and human bodies. So, they presented images drawn from independent data sets (that is, data sets that were not involved in training the network) that were known to be of cats, faces or bodies, and saw which parts of the network activated. By examining the activations within the network, they found that there were prototypes of cats, faces and bodies within the network. That is, they showed that the network had formed its own exemplars of these objects.
There are four main technical innovations in this paper:
1) The size of the network, which had one billion artificial neurons.
2) The technique they used to reduce the interconnections between the elements of the network, to make it easier to execute in parallel across the 16 000 processors they used.
3) The number of images (ten million) used to train the network.
4) The size of the images used (200 x 200 pixels, which is larger than most).
The network did not learn to recognise cats, faces, or bodies. It still doesn't know what a cat is, or what a face is, or what a human body is. It has no concept of what the images represent. But even so, it still has potential: neural networks have finally reached the age of Big Data.
Monday, June 25, 2012
Call for papers: ICANNGA 2013
The paper submission deadline for the International Conference on Adaptive and Natural Computing Algorithms (ICANNGA) 2013 is 8 October, 2013. This conference will be held in Lausanne, Switzerland, April 4-6, 2013.
Friday, June 22, 2012
Call for papers: AROB 2013
The deadline for submitting papers to the 18th International Symposium on Artificial Life and Robotics (AROB) 2013 is 1 September, 2012. This symposium will be held in Daejeon, Korea, January 30 - February 1st, 2013.
Thursday, June 21, 2012
Reminder: paper submission deadline for iFuzzy 2012
A reminder that the deadline for papers submitted to the International Conference on Fuzzy Theory and its Application 2012 is 20 August 2012. This conference will be held in Taiching, Tuiwan, 16-18 November, 2012.
Wednesday, June 20, 2012
Reminder: conference paper deadline for ICIIC 2012
A reminder that the paper submission deadline for the International Conference on Information and Intelligent Computing 2012 is 20 July 2012. This conference will be held in Chengdu, China, 8-9 December, 2012.
Tuesday, June 19, 2012
Paper submission deadline: EMO 2013
The deadline for submitting papers to the 7th International Conference on Evolutionary Multi-Criterion Optimization (EMO) 2013 is 19 August 2012. This conference will be held in Sheffield, UK, 19-22 March, 2013.
Monday, June 18, 2012
Call for papers: FOGA 2013
The deadline for submitting papers to the Foundations of Genetic Algorithms (FOGA) 2013 is 1 August 2012. This conference will be held in Adelaide, Australia, 16-20 January, 2013.
I am currently living in Adelaide, and can highly recommend a visit to this beautiful city. My only warning is that in January, the temperature often exceeds 40 degrees!
I am currently living in Adelaide, and can highly recommend a visit to this beautiful city. My only warning is that in January, the temperature often exceeds 40 degrees!
Friday, June 15, 2012
More developments in academic journals
There has been a new development in open-access academic journals (see my previous posts on this matter here, here, here, here and here). Two articles, here and here, describe PeerJ, a new approach to open-access journals. Whereas the traditional publishers charge readers for access to content, and open-access journals charge authors per-paper publication charges, PeerJ charges authors a one-off lifetime publishing fee. As long as all of the authors (or at least the first 12 authors) of a paper are subscribers, the authors can submit as many papers as they like for no further cost. The papers are peer-reviewed, and will be available for free. There are different subscriptions available, ranging from a lower-cost option that allows for a fixed number of papers per year, up to a more expensive "all you can eat" model with no restrictions.
PeerJ is starting with life sciences first: given the large number of researchers and papers coming out of the life sciences, this seems quite sensible and is more likely to give them a solid revenue stream early-on. It is interesting that they are requiring each member to review at least one paper per year, which neatly gets around the problems associated with finding enough reviewers for papers.
I suspect that the computational intelligence community does not have enough researchers to make such a model viable at the rates PeerJ are advertising. So, such a journal would probably have to charge higher subscription rates, or charge an annual or bi-annual fee.
But these are all ways for publishers to make money off of free content (submitted papers) and free labour, in the form of reviewers (who are actually paying for the privilege in the case of PeerJ). I'm not the first person to suggest this, but why not spend some of that money on reviewers? That is, when a reviewer completes an on-time review, pay them a small gratuity (like 100-200 Euros). That would motivate reviewers to do their reviews on time (if you're working for free, there is less motivation to do the work quickly). It would also be a more fair system, as those who provide the most valuable service in the publishing process would be compensated for their time and efforts. Finally, it might make it easier to find reviewers for papers: my own editorial experience has shown me how hard it can be to find reviewers for a paper. I review about a dozen papers per year, so this scheme wouldn't provide me with a living, but it would cover many of the incidental expenses that come up over the year.
Instead of a Boycott Elsevier pledge website, do we need a website where people can pledge to no longer review any papers until publishers start paying? Would anyone sign up for that?
PeerJ is starting with life sciences first: given the large number of researchers and papers coming out of the life sciences, this seems quite sensible and is more likely to give them a solid revenue stream early-on. It is interesting that they are requiring each member to review at least one paper per year, which neatly gets around the problems associated with finding enough reviewers for papers.
I suspect that the computational intelligence community does not have enough researchers to make such a model viable at the rates PeerJ are advertising. So, such a journal would probably have to charge higher subscription rates, or charge an annual or bi-annual fee.
But these are all ways for publishers to make money off of free content (submitted papers) and free labour, in the form of reviewers (who are actually paying for the privilege in the case of PeerJ). I'm not the first person to suggest this, but why not spend some of that money on reviewers? That is, when a reviewer completes an on-time review, pay them a small gratuity (like 100-200 Euros). That would motivate reviewers to do their reviews on time (if you're working for free, there is less motivation to do the work quickly). It would also be a more fair system, as those who provide the most valuable service in the publishing process would be compensated for their time and efforts. Finally, it might make it easier to find reviewers for papers: my own editorial experience has shown me how hard it can be to find reviewers for a paper. I review about a dozen papers per year, so this scheme wouldn't provide me with a living, but it would cover many of the incidental expenses that come up over the year.
Instead of a Boycott Elsevier pledge website, do we need a website where people can pledge to no longer review any papers until publishers start paying? Would anyone sign up for that?
Thursday, June 14, 2012
Publishing and perishing under gameable metrics 2
This article about the Australian Excellence in Research for Australia (ERA) initiative discusses how the process by which Australian universities and academic are assessed is flawed. It also discusses how Australian institutions have been gaming the metrics, like certain New Zealand institutions have been accused of doing.
In this previous post I described how any metric by which an institution or academic is assessed can be gamed. That is, any way in which an academic or institution is assessed can be manipulated by that institution to gain a higher score. In this post, I discussed how this has a negative effect on the teaching performance of an institution. By removing staff who do not perform well in research assessments due to a heavy teaching load, the institution can lift their research scores, but at the cost of lowering their teaching performance. As the article mentions, teaching is not assessed, so the process optimises towards a single metric at the expense of all others. This is not helpful for the long-term viability of an institution, as undergraduates will not want to attend an institution with a poor reputation for teaching.
This situation is almost certain to increase the use of contract lecturers, as contract lecturers are, as I understand it, exempt from assessment. I've already described why increasing contract lecturers is a bad idea, mostly because of a lack of job security and satisfaction for the contract lecturers, as well as a lack of continuity in teaching from the point of view of the students.
It is becoming increasingly apparent to me that assessing institutions is not as useful as assessing individuals, and that, in today's highly-mobile world, the reputation of an institution is no longer as important as the reputation of an individual researcher. This raises an interesting question:
What would happen if research performance based funding were given directly to the researchers based on their own individual performance, rather than their institutions being given extra funding based on the collective research performance of their staff?
The article linked at the start of this post does an excellent job of describing the problems with collective assessments (like what does it mean if you have one researcher ranked 1 and one ranked 5 - do they have a collective performance of 3? What does that even mean?).
Individual funding would remove a lot of the financial motivation for institutions to game the system, although it wouldn't eliminate it (institutions would still make money by charging the individual researchers over-heads, but these could be capped). Under the current Australian and New Zealand systems, individuals are assessed anyway, so it doesn't require any great changes to the current assessment process. One downside (and it could be a stonking big downside) is that early-career researchers would probably do poorly under this model. Early-career are already disadvantaged by management practices designed to game the system, and a simple weighting mechanism accounting for the length of time an individual has been doing research would go a long way to help. This would encourage researchers to start publishing early (which is essential to master the art of scientific publishing) and to publish consistently (which is essential to maintain your publishing skills). Another downside would be senior researchers taking credit for the work of junior researchers. But, again, this happens anyway, even though it is profoundly unethical. Under this system, though, it would no longer be just unethical, it would be criminal fraud.
Such a scheme could only be successful if it were paired with a scheme for assessing and rewarding teaching. While I have stated several times that an academic in a permanent position who is not publishing is not doing their job, an academic with a low (but not non-existent) research output and a strong teaching performance is an asset to an institution. Therefore, it is, in my opinion, imperative that an objective metric for teaching performance be implemented as soon as possible. That way, quality teachers, as well as quality researchers, would be recognised and rewarded. Those who do both (and this is the ideal for an academic, to teach and do research) would score even higher.
In this previous post I described how any metric by which an institution or academic is assessed can be gamed. That is, any way in which an academic or institution is assessed can be manipulated by that institution to gain a higher score. In this post, I discussed how this has a negative effect on the teaching performance of an institution. By removing staff who do not perform well in research assessments due to a heavy teaching load, the institution can lift their research scores, but at the cost of lowering their teaching performance. As the article mentions, teaching is not assessed, so the process optimises towards a single metric at the expense of all others. This is not helpful for the long-term viability of an institution, as undergraduates will not want to attend an institution with a poor reputation for teaching.
This situation is almost certain to increase the use of contract lecturers, as contract lecturers are, as I understand it, exempt from assessment. I've already described why increasing contract lecturers is a bad idea, mostly because of a lack of job security and satisfaction for the contract lecturers, as well as a lack of continuity in teaching from the point of view of the students.
It is becoming increasingly apparent to me that assessing institutions is not as useful as assessing individuals, and that, in today's highly-mobile world, the reputation of an institution is no longer as important as the reputation of an individual researcher. This raises an interesting question:
What would happen if research performance based funding were given directly to the researchers based on their own individual performance, rather than their institutions being given extra funding based on the collective research performance of their staff?
The article linked at the start of this post does an excellent job of describing the problems with collective assessments (like what does it mean if you have one researcher ranked 1 and one ranked 5 - do they have a collective performance of 3? What does that even mean?).
Individual funding would remove a lot of the financial motivation for institutions to game the system, although it wouldn't eliminate it (institutions would still make money by charging the individual researchers over-heads, but these could be capped). Under the current Australian and New Zealand systems, individuals are assessed anyway, so it doesn't require any great changes to the current assessment process. One downside (and it could be a stonking big downside) is that early-career researchers would probably do poorly under this model. Early-career are already disadvantaged by management practices designed to game the system, and a simple weighting mechanism accounting for the length of time an individual has been doing research would go a long way to help. This would encourage researchers to start publishing early (which is essential to master the art of scientific publishing) and to publish consistently (which is essential to maintain your publishing skills). Another downside would be senior researchers taking credit for the work of junior researchers. But, again, this happens anyway, even though it is profoundly unethical. Under this system, though, it would no longer be just unethical, it would be criminal fraud.
Such a scheme could only be successful if it were paired with a scheme for assessing and rewarding teaching. While I have stated several times that an academic in a permanent position who is not publishing is not doing their job, an academic with a low (but not non-existent) research output and a strong teaching performance is an asset to an institution. Therefore, it is, in my opinion, imperative that an objective metric for teaching performance be implemented as soon as possible. That way, quality teachers, as well as quality researchers, would be recognised and rewarded. Those who do both (and this is the ideal for an academic, to teach and do research) would score even higher.
Tuesday, June 12, 2012
International Neural Network Society Social Media sites
The International Neural Network Society (INNS) has established a presence on several popular social media
sites. The goals of this initiative are:
- To promote the membership and activities of the INNS
- To better bring the members of the INNS relevant information about the activities of the society
- To help facilitate networking between members
Members of the INNS and other interested people are invited join us on the following INNS social media sites:
Blog: http://innsorg.blogspot.com/
Twitter: http://www.twitter.com/#!/INNSorg
Facebook: http://www.facebook.com/pages/International-Neural-Network-Society/110873922384495
LinkedIn: http://www.linkedin.com/groups?gid=2985057
Google+: https://plus.google.com/106354210782755399208/posts
- To promote the membership and activities of the INNS
- To better bring the members of the INNS relevant information about the activities of the society
- To help facilitate networking between members
Members of the INNS and other interested people are invited join us on the following INNS social media sites:
Blog: http://innsorg.blogspot.com/
Twitter: http://www.twitter.com/#!/INNSorg
Facebook: http://www.facebook.com/pages/International-Neural-Network-Society/110873922384495
LinkedIn: http://www.linkedin.com/groups?gid=2985057
Google+: https://plus.google.com/106354210782755399208/posts
Friday, June 8, 2012
IEEE Transactions on Autonomous Mental Development, Vol.4, No.1, March 2012
1. Episodic-Like Memory for Cognitive Robots
Stachowicz, D.; Kruijff, G.M.
Page(s): 1-16
Digital Object Identifier: 10.1109/TAMD.2011.2159004
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5871687
2. A Model to Explain the Emergence of Imitation Development Based on Predictability Preference
Minato, T.; Thomas, D.; Yoshikawa, Y.; Ishiguro, H.
Page(s): 17-28
Digital Object Identifier: 10.1109/TAMD.2011.2158098
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5782935
3. Symbolic Models and Emergent Models: A Review
Juyang Weng
Page(s): 29-53
Digital Object Identifier: 10.1109/TAMD.2011.2159113
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5872008
4. A Behavior-Grounded Approach to Forming Object Categories: Separating Containers From Noncontainers
Griffith, S.; Sinapov, J.; Sukhoy, V.; Stoytchev, A.
Page(s): 54-69
Digital Object Identifier: 10.1109/TAMD.2011.2157504
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5778950
5. Autonomous Learning of High-Level States and Actions in Continuous Environments
Mugan, J.; Kuipers, B.
Page(s): 70-86
Digital Object Identifier: 10.1109/TAMD.2011.2160943
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5936108
6. A Goal-Directed Visual Perception System Using Object-Based Top-Down Attention
Yuanlong Yu; Mann, G.K.I.; Gosine, R.G.
Page(s): 87-103
Digital Object Identifier: 10.1109/TAMD.2011.2163513
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5978202
Stachowicz, D.; Kruijff, G.M.
Page(s): 1-16
Digital Object Identifier: 10.1109/TAMD.2011.2159004
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5871687
2. A Model to Explain the Emergence of Imitation Development Based on Predictability Preference
Minato, T.; Thomas, D.; Yoshikawa, Y.; Ishiguro, H.
Page(s): 17-28
Digital Object Identifier: 10.1109/TAMD.2011.2158098
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5782935
3. Symbolic Models and Emergent Models: A Review
Juyang Weng
Page(s): 29-53
Digital Object Identifier: 10.1109/TAMD.2011.2159113
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5872008
4. A Behavior-Grounded Approach to Forming Object Categories: Separating Containers From Noncontainers
Griffith, S.; Sinapov, J.; Sukhoy, V.; Stoytchev, A.
Page(s): 54-69
Digital Object Identifier: 10.1109/TAMD.2011.2157504
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5778950
5. Autonomous Learning of High-Level States and Actions in Continuous Environments
Mugan, J.; Kuipers, B.
Page(s): 70-86
Digital Object Identifier: 10.1109/TAMD.2011.2160943
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5936108
6. A Goal-Directed Visual Perception System Using Object-Based Top-Down Attention
Yuanlong Yu; Mann, G.K.I.; Gosine, R.G.
Page(s): 87-103
Digital Object Identifier: 10.1109/TAMD.2011.2163513
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5978202
Thursday, June 7, 2012
IEEE Transactions on Fuzzy Systems, vol. 20, issue 2, 2012
1. Human Gait Modeling Using a Genetic Fuzzy Finite State Machine
Author(s): Alvarez-Alvarez, A.; Trivino, G.; Cordon, O.
Page(s): 205 - 223
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6054027
2. An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System
Author(s): Hosseini, R.; Qanadli, S.D.; Barman, S.; Mazinani, M.; Ellis, T.; Dehmeshki, J.
Page(s): 224 - 234
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6054028
3. Exact Output Regulation for Nonlinear Systems Described by Takagi-Sugeno Fuzzy Models
Author(s): Meda-Campana, J.A.; Gomez-Mancilla, J.C.; Castillo-Toledo, B.
Page(s): 235 - 247
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6054029
4. A Linguistic Approach to Influencing Decision Behavior
Author(s): Petry, F.E.; Yager, R.R.
Page(s): 248 - 261
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6054030
5. Second-Order Sliding Fuzzy Interval Type-2 Control for an Uncertain System With Real Application
Author(s): Manceur, M.; Essounbouli, N.; Hamzaoui, A.
Page(s): 262 - 275
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6056561
6. Genetic Training Instance Selection in Multiobjective Evolutionary
Fuzzy Systems: A Coevolutionary Approach
Author(s): Antonelli, M.; Ducange, P.; Marcelloni, F.
Page(s): 276 - 290
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6061952
7. Fuzzy Time Series Forecasting With a Probabilistic Smoothing Hidden Markov Model
Author(s): Yi-Chung Cheng; Sheng-Tun Li
Page(s): 291 - 304
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6060907
8. T¨CS Fuzzy Model Identification With a Gravitational Search-Based Hyperplane Clustering Algorithm
Author(s): Chaoshun Li; Jianzhong Zhou; Bo Fu; Pangao Kou; Jian Xiao
Page(s): 305 - 317
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6061951
9. Exponential Stabilization for a Class of Nonlinear Parabolic PDE Systems via Fuzzy Control Approach
Author(s): Huai-Ning Wu; Jun-Wei Wang; Han-Xiong Li
Page(s): 318 - 329
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6061953
10. An Improved Input Delay Approach to Stabilization of Fuzzy Systems Under Variable Sampling
Author(s): Xun-Lin Zhu; Bing Chen; Dong Yue; Youyi Wang
Page(s): 330 - 341
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6064888
11. Reliable Fuzzy Control for Active Suspension Systems With Actuator Delay and Fault
Author(s): Hongyi Li; Honghai Liu; Huijun Gao; Peng Shi
Page(s): 342 - 357
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6064886
12. A Fuzzy Approach for Multitype Relational Data Clustering
Author(s): Jian-Ping Mei; Lihui Chen
Page(s): 358 - 371
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6068241
13. A Fuzzy System Constructed by Rule Generation and Iterative Linear SVR
for Antecedent and Consequent Parameter Optimization
Author(s): Chia-Feng Juang; Cheng-Da Hsieh
Page(s): 372 - 384
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6070980
14. A Novel Algorithm for Finding Reducts With Fuzzy Rough Sets
Author(s): Degang Chen; Lei Zhang; Suyun Zhao; Qinghua Hu; Pengfei Zhu
Page(s): 385 - 389
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6095617
15. Solving Fuzzy Relational Equations Via Semitensor Product
Author(s): Daizhan Cheng; Jun-e Feng; Hongli Lv
Page(s): 390 - 396
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6064885
16. On H¡Þ Filtering for Discrete-Time Takagi-Sugeno Fuzzy Systems
Author(s): Hui Zhang; Yang Shi; Mehr, A.S.
Page(s): 396 - 401
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6081923
Author(s): Alvarez-Alvarez, A.; Trivino, G.; Cordon, O.
Page(s): 205 - 223
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6054027
2. An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System
Author(s): Hosseini, R.; Qanadli, S.D.; Barman, S.; Mazinani, M.; Ellis, T.; Dehmeshki, J.
Page(s): 224 - 234
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6054028
3. Exact Output Regulation for Nonlinear Systems Described by Takagi-Sugeno Fuzzy Models
Author(s): Meda-Campana, J.A.; Gomez-Mancilla, J.C.; Castillo-Toledo, B.
Page(s): 235 - 247
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6054029
4. A Linguistic Approach to Influencing Decision Behavior
Author(s): Petry, F.E.; Yager, R.R.
Page(s): 248 - 261
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6054030
5. Second-Order Sliding Fuzzy Interval Type-2 Control for an Uncertain System With Real Application
Author(s): Manceur, M.; Essounbouli, N.; Hamzaoui, A.
Page(s): 262 - 275
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6056561
6. Genetic Training Instance Selection in Multiobjective Evolutionary
Fuzzy Systems: A Coevolutionary Approach
Author(s): Antonelli, M.; Ducange, P.; Marcelloni, F.
Page(s): 276 - 290
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6061952
7. Fuzzy Time Series Forecasting With a Probabilistic Smoothing Hidden Markov Model
Author(s): Yi-Chung Cheng; Sheng-Tun Li
Page(s): 291 - 304
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6060907
8. T¨CS Fuzzy Model Identification With a Gravitational Search-Based Hyperplane Clustering Algorithm
Author(s): Chaoshun Li; Jianzhong Zhou; Bo Fu; Pangao Kou; Jian Xiao
Page(s): 305 - 317
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6061951
9. Exponential Stabilization for a Class of Nonlinear Parabolic PDE Systems via Fuzzy Control Approach
Author(s): Huai-Ning Wu; Jun-Wei Wang; Han-Xiong Li
Page(s): 318 - 329
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6061953
10. An Improved Input Delay Approach to Stabilization of Fuzzy Systems Under Variable Sampling
Author(s): Xun-Lin Zhu; Bing Chen; Dong Yue; Youyi Wang
Page(s): 330 - 341
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6064888
11. Reliable Fuzzy Control for Active Suspension Systems With Actuator Delay and Fault
Author(s): Hongyi Li; Honghai Liu; Huijun Gao; Peng Shi
Page(s): 342 - 357
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6064886
12. A Fuzzy Approach for Multitype Relational Data Clustering
Author(s): Jian-Ping Mei; Lihui Chen
Page(s): 358 - 371
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6068241
13. A Fuzzy System Constructed by Rule Generation and Iterative Linear SVR
for Antecedent and Consequent Parameter Optimization
Author(s): Chia-Feng Juang; Cheng-Da Hsieh
Page(s): 372 - 384
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6070980
14. A Novel Algorithm for Finding Reducts With Fuzzy Rough Sets
Author(s): Degang Chen; Lei Zhang; Suyun Zhao; Qinghua Hu; Pengfei Zhu
Page(s): 385 - 389
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6095617
15. Solving Fuzzy Relational Equations Via Semitensor Product
Author(s): Daizhan Cheng; Jun-e Feng; Hongli Lv
Page(s): 390 - 396
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6064885
16. On H¡Þ Filtering for Discrete-Time Takagi-Sugeno Fuzzy Systems
Author(s): Hui Zhang; Yang Shi; Mehr, A.S.
Page(s): 396 - 401
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6081923
Tuesday, June 5, 2012
Final call for papers: INNS-WC 2012
The final deadline for submitting papers to the International Neural Network Society Winter Conference (INNS-WC) has been extended to 15 June 2012. This conference will be held in Bangkok, Thailand, October 3-5, 2012.
IEEE Transactions on Neural Networks and Learning Systems; Volume 23, Issue 6, June 2012
This issue published some papers on sparse representation, semi-supervised learning, spiking neural networks, high level classification, and multitask learning. We welcome you to submit your papers on these topics to IEEE TNNLS.
These articles can be retrieved on IEEE Xplore:
http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=6203443&punumber=5962385
or directly by clicking the individual paper URL below.
1. Title: Global Stability of Complex-Valued Recurrent Neural Networks With Time-Delays
Authors: Jin Hu; Jun Wang
Page(s): 853 - 865
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6194338
2. Title: Robust Exponential Stability of Uncertain Delayed Neural Networks With Stochastic Perturbation and Impulse Effects
Authors: Tingwen Huang; Chuandong Li; Shukai Duan; Janusz A. Starzyk
Page(s): 866 - 875
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6180003
3. Title: Sparse Tensor Discriminant Color Space for Face Verification
Authors: Su-Jing Wang; Jian Yang; Ming-Fang Sun; Xu-Jun Peng; Ming-Ming Sun; Chun-Guang Zhou
Page(s): 876 - 888
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6180223
4. Title: Programming Time-Multiplexed Reconfigurable Hardware Using a Scalable Neuromorphic Compiler
Authors: Kirill Minkovich; Narayan Srinivasa; Jose M. Cruz-Albrecht; Youngkwan Cho; Aleksey Nogin
Page(s): 889 - 901
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6182588
5. Title: Laplacian Embedded Regression for Scalable Manifold Regularization
Authors: Lin Chen; Ivor W. Tsang; Dong Xu
Page(s): 902 - 915
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6186826
6. Title: Neural Assembly Computing
Authors: João Ranhel
Page(s): 916 - 927
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6186825
7. Title: Extracting Representative Information to Enhance Flexible Data Queries
Authors: Jin Zhang; Guoqing Chen; Xiaohui Tang
Page(s): 928 - 941
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6189794
8. Title: Robust Synchronization for 2-D Discrete-Time Coupled Dynamical Networks
Authors: Jinling Liang; Zidong Wang; Xiaohui Liu; Panos Louvieris
Page(s): 942 - 953
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6191361
9. Title: Network-Based High Level Data Classification
Authors: Thiago Christiano Silva; Liang Zhao
Page(s): 954 - 970
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6192353
10. Title: Neural Network Structure for Spatio-Temporal Long-Term Memory
Authors: Vu Anh Nguyen; Janusz A. Starzyk; Wooi-Boon Goh; Daniel Jachyra
Page(s): 971 - 983
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6192329
11. Title: Feedback Optimal Control of Distributed Parameter Systems by Using Finite-Dimensional Approximation Schemes
Authors: Angelo Alessandri; Mauro Gaggero; Riccardo Zoppoli
Page(s): 984 - 996
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6192328
12. Title: Generalized SMO Algorithm for SVM-Based Multitask Learning
Authors: Feng Cai; Vladimir Cherkassky
Page(s): 997 - 1003
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6183517
13. Title: Complexity-Reduced Scheme for Feature Extraction With Linear Discriminant Analysis
Authors: Yuxi Hou; Iickho Song; Hwang-Ki Min; Cheol Hoon Park
Page(s): 1003 - 1009
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6191360
These articles can be retrieved on IEEE Xplore:
http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=6203443&punumber=5962385
or directly by clicking the individual paper URL below.
IEEE Transactions on Neural Networks and Learning Systems: Volume 23, Issue 6, June 2012
1. Title: Global Stability of Complex-Valued Recurrent Neural Networks With Time-Delays
Authors: Jin Hu; Jun Wang
Page(s): 853 - 865
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6194338
2. Title: Robust Exponential Stability of Uncertain Delayed Neural Networks With Stochastic Perturbation and Impulse Effects
Authors: Tingwen Huang; Chuandong Li; Shukai Duan; Janusz A. Starzyk
Page(s): 866 - 875
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6180003
3. Title: Sparse Tensor Discriminant Color Space for Face Verification
Authors: Su-Jing Wang; Jian Yang; Ming-Fang Sun; Xu-Jun Peng; Ming-Ming Sun; Chun-Guang Zhou
Page(s): 876 - 888
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6180223
4. Title: Programming Time-Multiplexed Reconfigurable Hardware Using a Scalable Neuromorphic Compiler
Authors: Kirill Minkovich; Narayan Srinivasa; Jose M. Cruz-Albrecht; Youngkwan Cho; Aleksey Nogin
Page(s): 889 - 901
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6182588
5. Title: Laplacian Embedded Regression for Scalable Manifold Regularization
Authors: Lin Chen; Ivor W. Tsang; Dong Xu
Page(s): 902 - 915
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6186826
6. Title: Neural Assembly Computing
Authors: João Ranhel
Page(s): 916 - 927
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6186825
7. Title: Extracting Representative Information to Enhance Flexible Data Queries
Authors: Jin Zhang; Guoqing Chen; Xiaohui Tang
Page(s): 928 - 941
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6189794
8. Title: Robust Synchronization for 2-D Discrete-Time Coupled Dynamical Networks
Authors: Jinling Liang; Zidong Wang; Xiaohui Liu; Panos Louvieris
Page(s): 942 - 953
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6191361
9. Title: Network-Based High Level Data Classification
Authors: Thiago Christiano Silva; Liang Zhao
Page(s): 954 - 970
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6192353
10. Title: Neural Network Structure for Spatio-Temporal Long-Term Memory
Authors: Vu Anh Nguyen; Janusz A. Starzyk; Wooi-Boon Goh; Daniel Jachyra
Page(s): 971 - 983
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6192329
11. Title: Feedback Optimal Control of Distributed Parameter Systems by Using Finite-Dimensional Approximation Schemes
Authors: Angelo Alessandri; Mauro Gaggero; Riccardo Zoppoli
Page(s): 984 - 996
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6192328
12. Title: Generalized SMO Algorithm for SVM-Based Multitask Learning
Authors: Feng Cai; Vladimir Cherkassky
Page(s): 997 - 1003
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6183517
13. Title: Complexity-Reduced Scheme for Feature Extraction With Linear Discriminant Analysis
Authors: Yuxi Hou; Iickho Song; Hwang-Ki Min; Cheol Hoon Park
Page(s): 1003 - 1009
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6191360
Thursday, May 31, 2012
An experiment in open-source textbooks 2
To further put my money where my mouth is, in regards to my support for open source textbooks, I'm following up Monday's post by making the outline of my open source textbook, Intelligent Information Systems, available online. The outline is in PDF format, and is available at the following address:
http://mike.watts.net.nz/IIS_Outline.pdf
Readers are encouraged to comment on the outline via the comments section of this blog - I want to hear your opinions!
http://mike.watts.net.nz/IIS_Outline.pdf
Readers are encouraged to comment on the outline via the comments section of this blog - I want to hear your opinions!
Wednesday, May 30, 2012
WCCI 2012 Panel Session on Computational Intelligence in Education and University Curricula
The following panel session at WCCI 2012 is organised by the IEEE Computational Intelligence Society's Curriculum Subcommittee (which I happen to serve on), and will be held Thursday, June 14, 4:10-5:10pm.
Chairs: Robert Kozma and Jennie Si
Panelists: Haibo He, Janusz Kaczprzyk, Jim Keller, Luis Magdalena, Marios Polycarpou, Lipo Wang
Computational Intelligence is a relatively new research field. A lot of educational materials have been created in various fields of CI in the past decades. However, due to the field's relatively youth, its fundamental achievements has not been organized into a comprehensive curriculum yet. It is crucial for the development of the field to have high-quality educational materials on the state of art of CI. This allows attracting and educating talented and enthusiastic students and documenting the progress in the field. The panel will discuss various areas of CI education, including existing databases and course materials, online resources and video lectures, development of new textbooks, open-source software, and others. Various recommendations for future actions will be discussed as well.
Chairs: Robert Kozma and Jennie Si
Panelists: Haibo He, Janusz Kaczprzyk, Jim Keller, Luis Magdalena, Marios Polycarpou, Lipo Wang
Computational Intelligence is a relatively new research field. A lot of educational materials have been created in various fields of CI in the past decades. However, due to the field's relatively youth, its fundamental achievements has not been organized into a comprehensive curriculum yet. It is crucial for the development of the field to have high-quality educational materials on the state of art of CI. This allows attracting and educating talented and enthusiastic students and documenting the progress in the field. The panel will discuss various areas of CI education, including existing databases and course materials, online resources and video lectures, development of new textbooks, open-source software, and others. Various recommendations for future actions will be discussed as well.
Tuesday, May 29, 2012
Reminder: paper submission deadline for AI'12
A reminder that the deadline for submitting papers to the 25th Australasian Joint Conference on Artificial Intelligence (AI) 2012 is 29 June, 2012. This conference will be held in Sydney, Australia, 4-7 December, 2012.
Monday, May 28, 2012
An experiment in open-source textbooks
I am thinking of writing a textbook. Actually, I'm working on three at the moment, one of which is a research monograph, but the one that it most relevant to this post is tentatively titled Intelligent Information Systems, and will cover neural networks, fuzzy systems and evolutionary algorithms at an undergraduate level. I also expect it would be useful for researchers from other disciplines who want to apply methods in computational intelligence to their own research, and to software engineers who want to solve real-world problems with computational intelligence.
In line with this post, I am seriously considering making Intelligent Information Systems available as an open-source textbook. But before I do, I need some encouragement. So I'm asking you, my dear readers, to encourage me. If you think you would assign an open-source textbook on this topic to a class, or that you would buy a self-published textbook, let me know in the comments. If you could see yourself contributing some other way, let me know, too.
It's up to you good folk to push me to do this!
In line with this post, I am seriously considering making Intelligent Information Systems available as an open-source textbook. But before I do, I need some encouragement. So I'm asking you, my dear readers, to encourage me. If you think you would assign an open-source textbook on this topic to a class, or that you would buy a self-published textbook, let me know in the comments. If you could see yourself contributing some other way, let me know, too.
It's up to you good folk to push me to do this!
Wednesday, May 23, 2012
Competition Call for IEEE CIS GOLDs and Students: Pitch your CI Research Idea and Win an iPad 2!!!
The following is cross-posted from the IEEE Computational Intelligence Society blog.
The CIS GOLD subcommittee is hosting a “Novel CI Research Idea Pitch” competition during the Student and GOLD reception at WCCI 2012 in Brisbane Australia.
Your Challenge: Design a one-page research proposal of your Computational Intelligence idea and get a chance to pitch your idea to a panel of CI experts and your peers using an “elevator pitch” (3 minute time limit). An “elevator pitch” is a short summary of a research idea. The research area must be “computational intelligence” and the participants must “sell” their idea to the judges to qualify for prizes. A panel of three CI experts will select 3 best pitches and the audience (your peers) will rank 1st, 2nd and 3rdwinner through secret ballot. Prizes will include 1 iPad for 1st winner, certificates and free full year IEEE CIS memberships. Register now for a chance to be heard!
Submission Guidelines: Interested GOLDs and Students should consult the full Brief and Submission Guidelines by going to http://tinyurl.com/cp8kdw8. Registration and submission deadline is June 11th 2012, Midnight EST. (You can register for the competition without submitting the research summary).
Register Now (Space is Limited!): http://tinyurl.com/7tror22
The CIS GOLD subcommittee is hosting a “Novel CI Research Idea Pitch” competition during the Student and GOLD reception at WCCI 2012 in Brisbane Australia.
Your Challenge: Design a one-page research proposal of your Computational Intelligence idea and get a chance to pitch your idea to a panel of CI experts and your peers using an “elevator pitch” (3 minute time limit). An “elevator pitch” is a short summary of a research idea. The research area must be “computational intelligence” and the participants must “sell” their idea to the judges to qualify for prizes. A panel of three CI experts will select 3 best pitches and the audience (your peers) will rank 1st, 2nd and 3rdwinner through secret ballot. Prizes will include 1 iPad for 1st winner, certificates and free full year IEEE CIS memberships. Register now for a chance to be heard!
Submission Guidelines: Interested GOLDs and Students should consult the full Brief and Submission Guidelines by going to http://tinyurl.com/cp8kdw8. Registration and submission deadline is June 11th 2012, Midnight EST. (You can register for the competition without submitting the research summary).
Register Now (Space is Limited!): http://tinyurl.com/7tror22
Tuesday, May 22, 2012
Publishing and perishing under gameable metrics
My alma mater is in the New Zealand news again, and again it is to do with gaming the metrics by which the research performance of New Zealand tertiary institutions are measured. This time, the article describes how many staff with poor publishing records have been made redundant from the university (that is, they have lost their jobs) prior to the assessment later this year. While I have little sympathy for those in permanent lecturing positions who do not publish (see my previous comments here and here) in this case it seems like the staff who have lost their jobs are predominantly teaching staff, or staff who are still developing their research record (see this post from one who lost her job for the same reason some time ago). If that is the case, then I have to say that the university administration is making a mistake.
Teaching takes a lot of time and energy (my last semester teaching at Otago, I was in the office at least six days a week, and often worked from 7:30 in the morning to 9 or 10 at night). The purpose of having teaching-only staff is to take some of that load off of the lecturers so that they can do their research. Indeed, the major thrust of the article is that the redundancies are putting more stress on the remaining staff, as they are having to pick up extra teaching in addition to lifting their own research outputs. While the teaching load could in theory be reduced by hiring contract lecturers (who would not, as I understand it, be assessed) I have already posted on why this is a bad idea.
From my research with evolutionary algorithms, I know that optimising to one criteria or metric seldom results in optimal or robust systems. By optimising their staff to one (flawed and gameable) metric, the University of Otago is reducing the robustness of their institution. The long-term outcome of these redundancies is yet to be seen, but I do not think that it will be good for anyone concerned. Non-performers need to be removed, for sure, but early-career researchers need coaching and leadership to develop. They don't need the great big stick stick of the threat of redundancy waved at them (such threats are more often than not a sign of dysfunctional management, rather than a sign of competent leadership).
Ultimately, only those who set the metrics can resolve this situation. As long as a metric can be gamed, then institutions will game them. In the meantime, people will have their lives upended and their careers destroyed by narrow-minded administrators and cynical political operators who are trying to wring a few more points out of the system to make themselves look good.
Teaching takes a lot of time and energy (my last semester teaching at Otago, I was in the office at least six days a week, and often worked from 7:30 in the morning to 9 or 10 at night). The purpose of having teaching-only staff is to take some of that load off of the lecturers so that they can do their research. Indeed, the major thrust of the article is that the redundancies are putting more stress on the remaining staff, as they are having to pick up extra teaching in addition to lifting their own research outputs. While the teaching load could in theory be reduced by hiring contract lecturers (who would not, as I understand it, be assessed) I have already posted on why this is a bad idea.
From my research with evolutionary algorithms, I know that optimising to one criteria or metric seldom results in optimal or robust systems. By optimising their staff to one (flawed and gameable) metric, the University of Otago is reducing the robustness of their institution. The long-term outcome of these redundancies is yet to be seen, but I do not think that it will be good for anyone concerned. Non-performers need to be removed, for sure, but early-career researchers need coaching and leadership to develop. They don't need the great big stick stick of the threat of redundancy waved at them (such threats are more often than not a sign of dysfunctional management, rather than a sign of competent leadership).
Ultimately, only those who set the metrics can resolve this situation. As long as a metric can be gamed, then institutions will game them. In the meantime, people will have their lives upended and their careers destroyed by narrow-minded administrators and cynical political operators who are trying to wring a few more points out of the system to make themselves look good.
Monday, May 21, 2012
The problem with academic journals: An update
A brief update on the status of the Elsevier boycott (described here): to date, more than 11 000 academics have pledged to not review, submit or do editorial work for any Elsevier journals. My previous post has already described why I oppose such a boycott of a single publisher, and I expect that this boycott is going to cause some unanticipated consequences.
I suspect that this boycott explains why the papers I have under review in Ecological Modelling and Ecological Informatics are taking so long to go through the review process: it's hard enough finding reviewers as it is, and with people refusing to review for Elsevier, it's going to get even harder. That's not punishing Elsevier, that's punishing the researchers who are trying to get their work published and advance their careers.
As I said before, the way real change will come about is by the top researchers supporting open-access journals. At least one of the people who could do this has just done so: Winston Hide, an associate editor at the highly-ranked Elsevier journal Genomics has just resigned from the editorial board, with the avowed intention of focusing his energies on open-access alternatives. I can only hope that some of the top researchers in computational intelligence will do the same.
I suspect that this boycott explains why the papers I have under review in Ecological Modelling and Ecological Informatics are taking so long to go through the review process: it's hard enough finding reviewers as it is, and with people refusing to review for Elsevier, it's going to get even harder. That's not punishing Elsevier, that's punishing the researchers who are trying to get their work published and advance their careers.
As I said before, the way real change will come about is by the top researchers supporting open-access journals. At least one of the people who could do this has just done so: Winston Hide, an associate editor at the highly-ranked Elsevier journal Genomics has just resigned from the editorial board, with the avowed intention of focusing his energies on open-access alternatives. I can only hope that some of the top researchers in computational intelligence will do the same.
Friday, May 18, 2012
Call for papers: INNS-WC 2012
INNS-WC2012 – 2012 International Neural Network Society Winter Conference
Bangkok, Thailand, October 3-5, 2012
http://inns.sit.kmutt.ac.th/wc2012/
Important Dates
Paper submission deadline: May 31, 2012
Notification of acceptance: June 30, 2012
Camera-ready paper: July 31, 2012
The 3rd International Neural Network Society Winter Conference (INNS-WC2012) will be held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012 aims to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline. INNS-WC2012 solicits contributions to the following tracks in natural and machine intelligence and related areas:
Prospective authors are invited to submit original, high quality manuscripts of up to twelve (12) pages electronically. Short papers of 4-6 pages will also be considered. The submission must conform to the Elsevier Procedia Computer Science format. All accepted papers will be published in the proceedings of INNS-WC2012 as anElsevier Procedia Computer Science open access volume (indexed by EI, Scopus and Conference Proceedings Citation Index - formerly ISI Proceedings). Extended version of selected papers may be invited for publication in special issues of international journals after the conference. All submissions will be checked by VeriGuide for originality.
The range of topics for the general conference track on
"Trends in Natural and Machine Intelligence" includes but is not limited to
The range of topics for the INNS Symposium on Nature Inspired Creativity (SoNIC2012) includes but is not limited to
The range of topics for the INNS Symposium on Vision and Image Processing (SoVIP2012) includes but is not limited to:
The range of topics for the INNS Symposium on Data Analytics and Competitions (SoDAC2012) includes but is not limited to:
Bangkok, Thailand, October 3-5, 2012
http://inns.sit.kmutt.ac.th/wc2012/
Important Dates
Paper submission deadline: May 31, 2012
Notification of acceptance: June 30, 2012
Camera-ready paper: July 31, 2012
The 3rd International Neural Network Society Winter Conference (INNS-WC2012) will be held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012 aims to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline. INNS-WC2012 solicits contributions to the following tracks in natural and machine intelligence and related areas:
- INNS-WC general track: Trends in Natural and Machine Intelligence
- INNS Symposium on Nature Inspired Creativity (SoNIC2012)
- INNS Symposium on Vision and Image Processing (SoVIP2012)
- INNS Symposium on Data Analytics and Competitions (SoDAC2012)
Prospective authors are invited to submit original, high quality manuscripts of up to twelve (12) pages electronically. Short papers of 4-6 pages will also be considered. The submission must conform to the Elsevier Procedia Computer Science format. All accepted papers will be published in the proceedings of INNS-WC2012 as anElsevier Procedia Computer Science open access volume (indexed by EI, Scopus and Conference Proceedings Citation Index - formerly ISI Proceedings). Extended version of selected papers may be invited for publication in special issues of international journals after the conference. All submissions will be checked by VeriGuide for originality.
The range of topics for the general conference track on
"Trends in Natural and Machine Intelligence" includes but is not limited to
- Autonomous machine learning
- Neural network theory & models
- Computational neuroscience
- Cognitive models
- Brain-machine interfaces
- Embodied robotics
- Evolutionary neural systems
- Neurodynamics
- Neuroinformatics
- Neuroengineering
- Neural hardware
- Neural network applications
- Pattern recognition
- Machine vision
- Speech science and technology
- Collective intelligence
- Hybrid systems
- Self-aware systems
- Data mining
- Sensor networks
- Agent-based systems
- Computational biology
- Bioinformatics
- Artificial life
SoNIC2012
The range of topics for the INNS Symposium on Nature Inspired Creativity (SoNIC2012) includes but is not limited to
- Application of Nature Inspired Computing in Creative Industries:
- Creative computing for digital media
- Computer aided design
- Computer generated special effects for film
- Cartoon animation
- Games
- Music
- Edutainment, etc.
- Art and Cognition:
- Art and the Brain
- Creative process
- Emotion and meaning in paintings, music, sculptures, poetry, etc.
- Generative Art:
- Systems that create drawings, images, animations, sculptures, poetry, text, graphic designs, musical pieces, sound-fonts, sound effects, film music, etc.
- Aesthetic evaluation:
- Aesthetic analysis of film, image, music, sound, sculpture, etc.
SoVIP2012
The range of topics for the INNS Symposium on Vision and Image Processing (SoVIP2012) includes but is not limited to:
- Low-level image processing
- Feature extraction and image description
- Image classification and clustering
- 3D sensing and depth measuring systems
- 3D object modeling and reconstruction
- Tracking and surveillance
- Motion estimation
- Human gesture recognition
- Human motion analysis
- Human face detection and tracking
- Human-robot interactions
- Robot intelligence
- Humanoid and mobile robotics
- Video indexing and retrieval
- Intelligent compression of massive imaging data
- Bio-medical imaging applications
- Bio-robotics
- Biometrics
SoDAC2012
The range of topics for the INNS Symposium on Data Analytics and Competitions (SoDAC2012) includes but is not limited to:
- Business intelligence
- Air quality and environmental issues
- Chemo-informatics
- Social networks and analytics
- Speech prosody
- Geo-informatics
- Neuro-informatics
- Internet and web analytics
- Data visualization techniques
- Data quality analysis
- Decision support and analytics
- Knowledge management and discovery
- Advanced database analytics
- Content and information retrieval
- Modeling and simulation of complex systems
- Optimization techniques
- Bio-data analysis
- Complex scheduling problems
- Scalability of data analysis
- Data competitions
Collocated Conferences
- The 3rd International Conference on Computational Systems-Biology and Bioinformatics (CSBio2012 - www.csbio.org)
- The 11th International Conference on Bioinformatics (InCoB2012 - www.incob2012.org)
Thursday, May 17, 2012
IEEE CIS Facebook Photo Competition
The IEEE Computational Intelligence Society are running a photo competition on Facebook. See the flyer below to find out how to enter.
Wednesday, May 16, 2012
Reminder: paper submission deadline for CISE 2012
A reminder that the deadline for papers submitted to the 4th International Conference on Computational Intelligence and Software Engineering (CISE) 2012 is 11 June 2012. This conference will be held in Wuhan, China, December 14-16, 2012.
Tuesday, May 15, 2012
Call for papers: Fuzz-IEEE 2013
The deadline for submitting papers to the IEEE Conference on Fuzzy Systems (Fuzz-IEEE) 2013 is 5 January, 2013. This conference will be held in Hyderabad, India, 7-10 July, 2013.
Monday, May 14, 2012
Call for papers: IJCNN 2013
The deadline for submitting papers to the IEEE International Joint Conference on Neural Networks (IJCNN) 2013 is February 1, 2013. This conference will be held in Dallas, Texas, August 4-9, 2013.
Friday, May 11, 2012
Call for papers: CEC 2013
The deadline for submitting papers to the IEEE Congress on Evolutionary Computation (CEC) 2013 is February 15, 2013. This conference will be held in Cancun, Mexico, June 20-23, 2013.
Thursday, May 10, 2012
Call for papers: EvoStar 2013
Wednesday, May 9, 2012
Deadline extension: UKCI 2012
The paper submission deadline for the 12th UK Annual Workshop on Computational Intelligence (UKCI) 2012 has been extended to May 31, 2012. This workshop will be held in Edinburgh, Scotland, UK, 5-7 September, 2012.
Wednesday, May 2, 2012
Reminder: conference paper deadline for NIPS 2012
A reminder that the deadline for submitting papers to Neural Information Processing Systems (NIPS) 2012 is 2 June 2012. This conference will be held at Lake Tahoe, Nevada, 3-6 December, 2012.
Tuesday, May 1, 2012
Reminder: submission deadline for ELM 2012
A reminder that the deadline for submitting papers to the International Symposium on Extreme Learning Machines (ELM) 2012 is 1 June, 2012. This symposium will be held in Singapore 11-13 December, 2012.
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