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.
Tuesday, July 24, 2012
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?
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