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

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

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

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.

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

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:

1. Fake data nobody ever expects to see
2. Work with many collaborators
3. Tell people what they already know
4. Don't do research anyone cares about
5. Don't publish in journals focused on your field
6. Distribute responsibility
7. Don't plagiarize
8. Don't duplicate images

It seems to me that, unfortunately, computational intelligence (CI) is more susceptible to many of these methods than many other fields. I sometimes joke that I am fortunate to work in a field where I can perform solid research by making stuff up as I go along, by which I mean that developing algorithms or techniques is often a more creative process than, for example, research in biology or physics. But think about how many CI papers you've seen that don't make the data available (point 1), or even describe its statistical parameters?

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.

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.

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.

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.

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.

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?

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

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.

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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!

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?

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.

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

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

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

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.

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

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!

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.

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.

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!

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.

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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

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.

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.

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:

• 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

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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.
  

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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

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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

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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)

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.

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.

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.

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.

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.

Call for papers: EvoStar 2013

The paper submission deadline for EvoStar 2013 is 1 November, 2012. This conference will be held in Vienna, Austria, 3-5 April, 2013.

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.

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.

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.

There's no un-gameable metric

I've been a bit quiet on the blog front lately, mostly because I've been working like a dog on several projects, including writing tools for ecological modelling, re-working some websites, and fulfilling my duties both as guest editor of my special issue of Evolving Systems on Applications of Evolving Connectionist Systems, and as vice-chair of the IEEE CIS Social Media Subcommittee. It was also school holidays the last two weeks here in South Australia, and I was able to spend some quality time with my little girl.

Never fear, I'm working on several new blog posts on a variety of topics, including: the relationship between computational intelligence and data mining; further thoughts on doing a PhD (a follow-up to this post); my thoughts on the value of a computational intelligence degree; and my thoughts on collaborating with other researchers. The topic of today's post, though, is assessing academics and universities.

My alma mater has been in the New Zealand news lately (see here and here) after the release of a report by accounting firm KPMG that suggests that Otago had gamed the New Zealand government research assessment process to give themselves a higher score than they were entitled to.

The Performance-Based Research Funding (PBRF) framework rates the research outputs of eligible staff and uses those ratings, along with metrics of institutional performance such as number of research degrees completed, to assign an overall score to the institution. Staff can be rated as R (research inactive - bad for this exercise), C (research active / good), B (very good) or A (world-class). The fewer R's and C's an institution has, and the more B's and A's, the better the institution's score. Something like 25-30% of an institution's income will be determined by this score. There is also the huge marketing advantage of an institution scoring highly in relation to the other universities: in the first PBRF round in 2004, Auckland University made a lot of the fact that their staff were, on average, ranked highest in the country, while Otago made a lot of the fact that they were ranked highest as an institution. This is despite the government of the day clearly saying that PBRF wasn't supposed to be used for such comparisons, or as a management tool.

Eagle-eyed readers may have noticed the term "eligible staff" earlier in the previous paragraph: it is this facet of the process that Otago is accused of gaming.

The accusation is that Otago inappropriately classified staff it knew would get low scores as ineligible for assessment, and thus artificially boosted its ranking compared to other New Zealand institutions. Otago is also accused of firing, or pushing into retirement, staff based on their anticipated PBRF score. The vice-chancellor denies these accusations, and the whole thing is turning into a "he said / she said" situation.

Did Otago really do this? I honestly don't know. I do know that when I was working at Otago in 2004 (the first PBRF assessment round), I was assessed fully, and fairly, even though it would have been pretty easy to classify me as ineligible for assessment. I don't think my score in PBRF at the time was particularly helpful to their overall ranking, but maybe it wasn't too harmful, either. My point is, this entire drama shows that there is no metric of academic performance, of an individual, an institution, or a publication, that can't be gamed. That is, there is no metric that can't be manipulated so that an individual, institution or publication gets a higher score than they otherwise would. Journals can boost their impact factor by asking authors to cite articles from within that publication (and I have had editors ask me to do this). Individuals can boost their h-index by auto-citations, or by organising a special issue and asking every author to cite a review article they have written. Institutions can raise their assessment by head-hunting the top-performers in their fields, or by hiding staff from assessment. Some might argue that it is only prudent to game metrics whenever possible: after all, the future employment prospects of an academic, or the future financial security (and, therefore, job security of staff of) an institution depends on getting a good score on whatever metric is being used. As long as no rules are being broken, and the questions are being answered honestly, what's the harm? If there is wiggle-room, or room for gaming of the metric, isn't it the assessor's fault for designing an inexact metric? Others might argue that adherence to the spirit of the assessment is more important, more fair, and that gaming should be avoided.

This all means that there is no one metric you can use to assess an academic. You have to look at the entire picture: you have to look at their publication count; where they have published; what fields they have published in; how much teaching they have done; their teaching assessments; the quality of their institution; and their service to their institution(s), to professional societies, and to the community. I hope that one day I will rate highly in all of those areas, but for now, don't judge me just by my h-index alone.

The future of universities

Or, why contract lecturers are probably a bad idea.

The last time I was job-hunting, I noticed a number of positions advertised as "sessional" or "contract" lecturers. These were positions where a person would present a few lectures a week for a certain course, for a fixed period of time, then leave the institution. In this article, the use of contract lecturers in American universities is described as a crisis, where quality of teaching is suffering and the highly-skilled educators end up severely under-paid. While administrators justify this as a way of cutting monetary costs, the educational costs are huge.

Firstly, contract lecturers are not available for struggling students. This is because they are seldom paid full-time, which makes it difficult to find time for out-of-class student consultation: people don't like to work for nothing.

Secondly, the fly-by-night nature of contract lecturers prevents them from forging bonds with cohorts of students: the students see them for one course, then never see them again. In other words, the contract lecturer has no motivation and little opportunity to see their students as anything other than faceless blobs that sit in the lectures absorbing information. This is not conducive to high-quality teaching.

This also makes it harder to recruit post-graduate students. I vividly remember the first time I was lectured by the man who would go on to be my PhD supervisor: I was a first-year undergraduate, sitting in a lecture theatre on a cold Dunedin evening, and he described a world of computational intelligence that I knew right then was a world I wanted to explore myself. I knew that if I worked hard in my first and second year courses, I would be able to do his third-year honours-track course, and if I did well in third-year, I could do his fourth-year honours course, and if I did well in that, I could do a PhD with him. If he had been a fly-by-night contract lecturer, would I have been as inspired? I probably would have skipped honours and gone into the workforce straight after third year. While that might have placed me in a slightly better financial position, my life would be much less rich than it is now.

While I don't have evidence for it, I suspect that contract lecturing does not overall attract the best teaching talent. Now, I'm not trying to denigrate contract lecturers, and I know several people who have worked as contract lecturers to support themselves while looking for post-docs, immediately after completing their PhDs. But as a highly-trained professional (which is what anyone with a PhD is) it is hard to justify taking a contract lecturer position if there are any other options available. I never even bothered applying for the contract lecturing positions I saw advertised, even though I was capable of doing them well, simply because it was not worth my while to shift myself and my family to do the job. If I were a single man, perhaps I could embrace the digital nomad lifestyle, and drift about doing contract lecturing here and there. But with a family to support, including a primary-school age daughter, it simply is not an option.

On the flip side, contract lecturing can provide a way for junior staff to get some experience lecturing. Also, technology is getting to the point where the lecturer no longer has to be in the same physical location as the class: the success of the Khan Academy and open courses (like the courses run by Sebastian Thrun) has shown that it is possible to have a class that is far away from the instructors. If the option to teach remotely were there, it might be easier to get top-talent as contract lecturers. I wouldn't mind being a contract lecturer if it meant I didn't have to relocate. That is, I wouldn't mind the job so much if I didn't have to move to do it. Of course, the alienation between lecturer and student that I discussed above could become even greater.

I think that the use of contract lecturers is probably going to increase, especially for first-year or general "service" courses, like for introductory programming or basic web development. But for more advanced under-graduate courses, or for post-graduate teaching, permanent staff are absolutely essential, due to the multi-year nature of post-graduate study. This also requires a level of specialisation that contract lecturers simply cannot develop: they are treated like interchangeable parts, which is no way to treat anyone, let alone someone who you expect to teach, and to inspire, students.

Reminder: paper submission deadline for CIDU 2012

A reminder that the deadline for submitting papers to the 2012 Conference on Intelligent Data Understanding (CIDU) 2012 is 18 May 2012. This conference will be held in Boulder, Colorado, 24-26 October, 2012.

Special session: Computational Intelligence and Social Media

The below is a call for papers for a special session of the 2012  IEEE Workshop on Computational Intelligence for Security and Defence Applications (IEEE CISDA) 2012. The deadline for submitting papers for this special session is 23 April, 2012. This conference will be held in Ottawa, Canada, 11-13 July 2012.

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Computational Intelligence and Social Media

Organizers: John Verdon, DRDC Ottawa, Canada
Contact: john.verdon -at- drdc-rddc.gc.ca

Military and security communities are hard-pressed to develop the capabilities required to exploit the huge volumes of data, the new forms of information, and rapidly changing content of Social Media (SM) such as blogs, wikis, videos, social graph based systems (such as Facebook, Twitter) and many other SM systems that are being deployed. SM is also in its infancy, so there is a huge potential for SM to evolve far beyond its current capabilities and types of information.

Computational Intelligence techniques (Neural network, Evolutionary computation, Fuzzy Systems, Particle Swarms, etc) have often been based on, and and have been related to, highly complex, structured, and dynamic natural systems in [biology, neuroscience, brain, psychology, sociology]. This may make them particularly well suited for the extraction of intelligence from existing forms of SM, for the [modeling, prediction, control] of SM activity, as well as for providing some capability of keeping up with rapidly evolving and new forms of SM. Papers that deal with massive datasets are of particular interest, and, naturally, papers should relate to defense and security needs, applications, and tool-sets. Security & Defense needs and Social Media [some examples from Forrester 2011, Verdon 2012] topics include, but are not limited to:

• Language translation - filtering a collection of documents down to those that should be translated by humans
• Knowledge extraction - validating facts from unstructured and questionable sources
• Document summarization - extracting the sense of a document or a group of topically-related documents, and establishing the main points of consensus and divergence
• Trend identification - as well as possible causal linkages among trends and supporting evidence
• Active learning - determining where information is lacking and which data would be most productive to acquire
• Security - at what threshold does secrecy become a liability rather than an asset for security?
• Reputation and/or Recommendation - ‘quick trust’ of the participants and possibly of the information