Reminder: paper submission deadline for ICONIP 2013

A reminder that the paper submission deadline for the 20th International Conference on Neural Information Processing (ICONIP) 2013 is 1 June 2013. This conference will be held in Daegu, Korea, 3-7 November, 2013.

Reminder: conference paper deadline for ICACI 2013

A reminder that the deadline for submitting papers to the International Conference on Advanced Computational Intelligence (ICACI) 2013 is June 1 2013. This conference will be held in Hangzhou, China, 19-21 October, 2013.

Neural Networks Volume 42 June 2013

Cognitive Science

1. Discriminant subspace learning constrained by locally statistical uncorrelation for face recognition
Author(s): Yu Chen, Wei-Shi Zheng, Xiao-Hong Xu, Jian-Huang Lai
Pages: 28-43
http://www.sciencedirect.com/science/article/pii/S0893608013000130

Learning Systems

2. Probabilistic DHP adaptive critic for nonlinear stochastic control systems
Author(s): Randa Herzallah
Pages: 74-82
http://www.sciencedirect.com/science/article/pii/S0893608013000294

3. Learning in compressed space
Author(s): Alexander Fabisch, Yohannes Kassahun, Hendrik Wöhrle, Frank Kirchner
Pages: 83-93
http://www.sciencedirect.com/science/article/pii/S089360801300035X


Mathematical and Computational Analysis

4. Wavelet neural networks: A practical guide
Author(s): Antonios K. Alexandridis, Achilleas D. Zapranis
Pages: 1-27
http://www.sciencedirect.com/science/article/pii/S0893608013000129

5. A model of analogue K-winners-take-all neural circuit
Author(s): Pavlo V. Tymoshchuk
Pages: 44-61
http://www.sciencedirect.com/science/article/pii/S0893608013000282


Engineering and Applications

6. Synthesis of high-complexity rhythmic signals for closed-loop electrical neuromodulation
Author(s): Osbert C. Zalay, Berj L. Bardakjian
Pages: 62-73
http://www.sciencedirect.com/science/article/pii/S0893608013000099

Neural Networks Special Issue CFP

Affective and Cognitive Learning Systems for Big Social Data Analysis

 

Guest Editors
Amir Hussain (Lead Guest Editor), University of Stirling, United Kingdom (ahu@cs.stir.ac.uk)
Erik Cambria, National University of Singapore, Singapore (cambria@nus.edu.sg)
Björn Schuller, Technische Universität München, Germany (schuller@tum.de)
Newton Howard, MIT Media Laboratory, USA (nhmit@mit.edu)

Background and Motivation
As the Web rapidly evolves,Web users are evolving with it. In an era of social connectedness, people are becoming more and more enthusiastic about interacting, sharing, and collaborating through social networks, online communities, blogs, Wikis, and other online collaborative media. In recent years, this collective intelligence has spread to many different areas, with particular focus on fields related to everyday life such as commerce, tourism, education, and health, causing the size of the Web to expand exponentially. The distillation of knowledge from such a large amount of unstructured information, however, is an extremely difficult task, as the contents of today’s Web are perfectly suitable for human consumption, but remain hardly accessible to machines. The opportunity to capture the opinions of the general public about social events, political movements, company strategies, marketing campaigns, and product preferences has raised growing interest both within the scientific community, leading to many exciting open challenges, as well as in the business world, due to the remarkable benefits to be had from marketing and financial market prediction.

 

Existing approaches to opinion mining mainly rely on parts of text in which sentiment is explicitly expressed, e.g., through polarity terms or affect words (and their co-occurrence frequencies). However, opinions and sentiments are often conveyed implicitly through latent semantics, which make purely syntactical approaches ineffective. In this light, this Special Issue focuses on the introduction, presentation, and discussion of novel techniques that further develop and apply big data analysis tools and techniques for sentiment analysis. A key motivation for this Special Issue, in particular, is to explore the adoption of novel affective and cognitive learning systems to go beyond a mere word-level analysis of natural language text and provide novel concept-level tools and techniques that allow a more efficient passage from (unstructured) natural language to (structured) machine-processable data, in potentially any domain.

 

Articles are thus invited in areas such as machine learning, weakly supervised learning, active learning, transfer learning, deep neural networks, novel neural and cognitive models, data mining, pattern recognition, knowledge-based systems, information retrieval, natural language processing, and big data computing. Topics include, but are not limited to:

• Machine learning for big social data analysis
• Biologically inspired opinion mining
• Semantic multi-dimensional scaling for sentiment analysis
• Social media marketing
• Social media analysis, representation, and retrieval
• Social network modeling, simulation, and visualization
• Concept-level opinion and sentiment analysis
• Patient opinion mining
• Sentic computing
• Multilingual sentiment analysis
• Time-evolving sentiment tracking
• Cross-domain evaluation
• Domain adaptation for sentiment classification
• Multimodal sentiment analysis
• Multimodal fusion for continuous interpretation of semantics
• Human-agent, -computer, and -robot interaction
• Affective common-sense reasoning
• Cognitive agent-based computing
• Image analysis and understanding
• User profiling and personalization
• Affective knowledge acquisition for sentiment analysis

The Special Issue also welcomes papers on specific application domains of big social data analysis, e.g., influence networks, customer experience management, intelligent user interfaces, multimedia management, computer-mediated human-human communication, enterprise feedback management, surveillance, art. The authors will be required to follow the Author’s Guide for manuscript submission to Elsevier Neural Networks.

Timeframe
Call for Papers out: April 2013
Submission Deadline: August 1, 2013
Notification of Acceptance: November 1, 2013
Final Manuscripts Due: December 1, 2013
Date of Publication: March 2014

Composition and Review Procedures
The Elsevier Neural Networks Special Issue on Affective and Cognitive Learning Systems for Big Social Data Analysis will consist of papers on novel methods and techniques that further develop and apply big data analysis tools and techniques in the context of opinion mining and sentiment analysis. Some papers may survey various aspects of the topic. The balance between these will be adjusted to maximize the issue’s impact. All articles are expected to successfully negotiate the standard review procedures for Elsevier Neural Networks. Authors are required to follow Elsevier Neural Networks proceedings templates and to submit their manuscripts at http://ees.elsevier.com/neunet.

Reminder: paper submission deadline: AAIA 2013

A reminder that the deadline for submitting papers to the 8th International Symposium Advances in Artificial Intelligence and Applications is 12 May 2013. This conference will be held in Krakow, Poland, 8-11 September 2013.

Neural Networks: New articles 2-8 April, 2013

1. Discriminant subspace learning constrained by locally statistical uncorrelation for face recognition
Author(s): Yu Chen, Wei-Shi Zheng, Xiao-Hong Xu, Jian-Huang Lai
Pages: 28-43

2. Probabilistic DHP adaptive critic for nonlinear stochastic control systems
Author(s): Randa Herzallah
Pages: 74-82

3. Learning in compressed space
Author(s): Alexander Fabisch, Yohannes Kassahun, Hendrik Wöhrle, Frank Kirchner
Pages: 83-93

4. Wavelet neural networks: A practical guide
Author(s): Antonios K. Alexandridis, Achilleas D. Zapranis
Pages: 1-27

5. A model of analogue winners-take-all neural circuit
Author(s): Pavlo V. Tymoshchuk
Pages: 44-61

6. Synthesis of high-complexity rhythmic signals for closed-loop electrical neuromodulation
Author(s): Osbert C. Zalay, Berj L. Bardakjian
Pages: 62-73

IEEE Transactions on Fuzzy Systems: Volume 21 Issue 2 April 2013

1. Stationary Fuzzy Fokker–Planck Learning for Derivative-Free Optimization
Author(s): Kumar, M. ; Stoll, N. ; Thurow, K. ; Stoll, R.
Page(s): 193 - 208
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6216407

2. Weighted Fuzzy Spiking Neural P Systems
Author(s): Wang, J. ; Shi, P. ; Peng, H. ; Perez-Jimenez, M.J. ; Wang, T.
Page(s): 209 - 220
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6242397

3. Fault Estimation and Tolerant Control for Fuzzy Stochastic Systems
Author(s): Liu, M. ; Cao, X. ; Shi, P.
Page(s): 221 - 229
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6243202

4. Interval Type-2 Fuzzy Sets Constructed From Several Membership Functions: Application to the Fuzzy Thresholding Algorithm
Author(s): Pagola, M. ; Lopez-Molina, C. ; Fernandez, J. ; Barrenechea, E. ; Bustince, H.
Page(s): 230 - 244
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6247495

5. Static-Output-Feedback {maths\cr H}_{bm \infty } Control of Continuous-Time T–S Fuzzy Affine Systems Via Piecewise Lyapunov Functions
Author(s): Qiu, J. ; Feng, G. ; Gao, H.
Page(s): 245 - 261
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6252027

6. Output Regulation of Polynomial-Fuzzy-Model-Based Control Systems
Author(s): Lam, H.K. ; Lo, J.C.
Page(s): 262 - 274
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6257463

7. Adaptive Fuzzy Control via Observer Design for Uncertain Nonlinear Systems With Unmodeled Dynamics
Author(s): Liu, Y.-J. ; Tong, S.C. ; Chen, C.L.P.
Page(s): 275 - 288
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6262470

8. Fuzzy Logic System-Based Adaptive Fault-Tolerant Control for Near-Space Vehicle Attitude Dynamics With Actuator Faults
Author(s): Shen, Q. ; Jiang, B. ; Cocquempot, V.
Page(s): 289 - 300
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6268340

10. Adaptive Output Feedback Control for Nonlinear Time-Delay Systems by Fuzzy Approximation Approach
Author(s): Zhou, Q. ; Shi, P. ; Xu, S. ; Li, H.
Page(s): 301 - 313
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6269079

11. A Combined Backstepping and Stochastic Small-Gain Approach to Robust Adaptive Fuzzy Output Feedback Control
Author(s): Tong, S. ; Wang, T. ; Li, Y. ; Chen, B.
Page(s): 314 - 327
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6269080

12. Universal Fuzzy Models and Universal Fuzzy Controllers for Stochastic Nonaffine Nonlinear Systems
Author(s): Gao, Q. ; Feng, G. ; Wang, Y. ; Qiu, J.
Page(s): 328 - 341
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6272339

13. Intuitionistic Fuzzy Cognitive Maps
Author(s): Papageorgiou, E.I. ; Iakovidis, D.K.
Page(s): 342 - 354
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6275486

14. Parallel Distributed Hybrid Fuzzy GBML Models With Rule Set Migration and Training Data Rotation
Author(s): Ishibuchi, H. ; Mihara, S. ; Nojima, Y.
Page(s): 355 - 368
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6287013

15. Differential Neuro-Fuzzy Controller for Uncertain Nonlinear Systems
Author(s): Chairez, I.
Page(s): 369 - 384
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6289361

16. Switching-Type H_{\infty } Filter Design for T–S Fuzzy Systems With Unknown or Partially Unknown Membership Functions
Author(s): Li, X-.J. ; Yang, G-.H.
Page(s): 385 - 392
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6265386

IEEE Transactions on Neural Networks and Learning Systems: Volume 24, Issue 5, May 2013

1. Nonstationary Source Separation Using Sequential and Variational Bayesian Learning
Author(s): Chien, J.-T. ; Hsieh, H.-L.
Page(s): 681 - 694
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6449323

2. Complex-Valued Filtering Based on the Minimization of Complex-Error Entropy
Author(s): Huang, S. ; Li, C. ; Liu, Y.
Page(s): 695 - 708
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6450100

3. Multiview Vector-Valued Manifold Regularization for Multilabel Image Classification
Author(s): Luo, Y. ; Tao, D. ; Xu, C. ; Xu, C. ; Liu, H. ; Wen, Y.
Page(s): 709 - 722
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6459040

4. Stopped Object Detection by Learning Foreground Model in Videos
Author(s): Maddalena, L. ; Petrosino, A.
Page(s): 723 - 735
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6459038

5. Asynchronous Cellular Automaton-Based Neuron: Theoretical Analysis and On-FPGA Learning
Author(s): Matsubara, T. ; Torikai, H.
Page(s): 736 - 748
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6459039

6. Soft Margin Multiple Kernel Learning
Author(s): Xu, X. ; Tsang, I.W. ; Xu, D.
Page(s): 749 - 761
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6459603

7. Online Learning Control Using Adaptive Critic Designs With Sparse Kernel Machines
Author(s): Xu, X. ; Hou, Z. ; Lian, C. ; He, H.
Page(s): 762 - 775
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6461419

8. Policy Improvement by a Model-Free Dyna Architecture
Author(s): Hwang, K.-S. ; Lo, C.-Y.
Page(s): 776 - 788
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6463457

9. Firing Rate Propagation Through Neuronal–Astrocytic Network
Author(s): Liu, Y. ; Li, C.
Page(s): 789 - 799
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6464601

10. On Stabilization of Stochastic Cohen-Grossberg Neural Networks With Mode-Dependent Mixed Time-Delays and Markovian Switching
Author(s): Zheng, C.-D. ; Shan, Q.-H. ; Zhang, H. ; Wang, Z.
Page(s): 800 - 811
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6477186

11. A One-Layer Projection Neural Network for Nonsmooth Optimization Subject to Linear Equalities and Bound Constraints
Author(s): Liu, Q. ; Wang, J.
Page(s): 812 - 824
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6472077

12. Constraint Verification With Kernel Machines
Author(s): Gori, M. ; Melacci, S.
Page(s): 825 - 831
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6461129

13. Energy-Efficient SVM Learning Control System for Biped Walking Robots
Author(s): Wang, L. ; Liu, Z. ; Chen, C.L.P. ; Zhang, Y. ; Lee, S. ; Chen, X.
Page(s): 831 - 837
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6461130

14. Self-Tuning Control With a Filter and a Neural Compensator for a Class of Nonlinear Systems
Author(s): Fu, Y. ; Chai, T.
Page(s): 837 - 843
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6469238

IEEE Transactions on Evolutionary Computation: Volume 17 Issue 2 2013

1. Guest Editorial: Special Issue on Understanding Complex Evolutionary Systems
Author(s): Ashlock, D. ; Kendall, G. ; Chong, S.
Page(s): 153 - 154
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6488784

2. Complex Coevolutionary Dynamics—Structural Stability and Finite Population Effects
Author(s): Tino, P. ; Chong, S.Y. ; Yao, X.
Page(s): 155 - 164
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6449315

3. Visualizing Mutually Nondominating Solution Sets in Many-Objective Optimization
Author(s): Walker, D.J. ; Everson, R.M. ; Fieldsend, J.E.
Page(s): 165 - 184
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6342906

4. Evolved Features for DNA Sequence Classification and Their Fitness Landscapes
Author(s): Ashlock, W. ; Datta, S.
Page(s): 185 - 197
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6232454

5. Fitness Landscapes of Evolved Apoptotic Cellular Automata
Author(s): Ashlock, D. ; McNicholas, S.
Page(s): 198 - 212
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6463449

6. Coevolving Game-Playing Agents: Measuring Performance and Intransitivities
Author(s): Samothrakis, S. ; Lucas, S. ; Runarsson, T.P. ; Robles, D.
Page(s): 213 - 226
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6242396

7. Agent-Case Embeddings for the Analysis of Evolved Systems
Author(s): Ashlock, D. ; Lee, C.
Page(s): 227 - 240
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6384730

8. Particle Swarm Optimization With an Aging Leader and Challengers
Author(s): Chen, W.-N. ; Zhang, J. ; Lin, Y. ; Chen, N. ; Zhan, Z.-H. ; Chung, H.S.-H. ; Li, Y. ; Shi, Y.-H.
Page(s): 241 - 258
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6151121

9. Experimental Analysis of Bound Handling Techniques in Particle Swarm Optimization
Author(s): Helwig, S. ; Branke, J. ; Mostaghim, S.M.
Page(s): 259 - 271
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6163405

10. FPGA Implementation of an Evolutionary Algorithm for Autonomous Unmanned Aerial Vehicle On-Board Path Planning
Author(s): Kok, J. ; Gonzalez, L.F. ; Kelson, N.
Page(s): 272 - 281
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6175116

Neural Networks: New articles 20-26 March 2013

1. Intelligence and embodiment: A statistical mechanics approach
Pages: 52-72
Author(s): Alejandro Chinea, Elka Korutcheva

2. Modulation of spike and burst rate in a minimal neuronal circuit with feed-forward inhibition
Pages: 1-17
Author(s): Fleur Zeldenrust, Wytse J. Wadman

3. Modeling the electrical field created by mass neural activity
Pages: 44-51
Author(s): Eran Privman, Rafael Malach, Yehezkel Yeshurun

4. Synchronization of two Hindmarsh–Rose neurons with unidirectional coupling
Pages: 73-79
Author(s): Dalibor Hrg

5. Training multi-layered neural network neocognitron
Pages: 18-31
Author(s): Kunihiko Fukushima

6. Extraction of primitive representation from captured human movements and measured ground reaction force to generate physically consistent imitated behaviors
Pages: 32-43
Author(s): Yuka Ariki, Sang-Ho Hyon, Jun Morimoto

Reminder: paper submission deadline for ICARIS 2013

A reminder that the deadline for submitting papers to the 12th International Conference on Artificial Immune Systems (ICARIS) 2013 is 22 April 2013. This conference will be held in Nottingham, UK, 27-29 August 2013.

IEEE Transactions on Autonomous Mental Development: Volume 5, Issue 1, 2013

1. The Coordinating Role of Language in Real-Time Multimodal Learning of Cooperative Tasks
Author(s): Petit, M. ; Lallee, S. ; Boucher, J.-D. ; Pointeau, G. ; Cheminade, P. ; Ognibene, D. ; Chinellato, E. ; Pattacini, U. ; Gori, I. ; Martinez-Hernandez, U. ; Barron-Gonzalez, H. ; Inderbitzin, M. ; Luvizotto, A. ; Vouloutsi, V. ; Demiris, Y. ; Metta, G. ; Dominey, P.F.
Page(s): 3 - 17
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6249732

2. A Survey of the Ontogeny of Tool Use: From Sensorimotor Experience to Planning
Author(s): Guerin, F. ; Kruger, N. ; Kraft, D.
Page(s): 18 - 45
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6248675

3. Learning Information Acquisition for Multitasking Scenarios in Dynamic Environments
Author(s): Karaoguz, C. ; Rodemann, T. ; Wrede, B. ; Goerick, C.
Page(s): 46 - 61
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6341054

4. A Spike-Based Model of Neuronal Intrinsic Plasticity
Author(s): Li, C. ; Li, Y.
Page(s): 62 - 73
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6257429

5. Autonomous and Interactive Improvement of Binocular Visual Depth Estimation through Sensorimotor Interaction
Author(s): Mann, T.A. ; Park, Y. ; Jeong, S. ; Lee, M. ; Choe, Y.
Page(s): 74 - 84
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6293858

6. Erratum to "Human-Recognizable Robotic Gestures" [Dec 12 305-314]
Author(s): Cabibihan, J.-J. ; So, W.-C. ; Pramanik, S.
Page(s): 85
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6479278

IEEE Transactions on Computational Intelligence and AI in Games: Volume 5, Issue 1, 2013

1. A Neurally Controlled Computer Game Avatar With Humanlike Behavior
Author(s): Gamez, D. ; Fountas, Z. ; Fidjeland, A.K.
Page(s): 1 - 14
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6357232

2.  Designing Automated Allocation Mechanisms for Service Procurement of Imperfectly Substitutable Services
Author(s): Kruse, S. ; Brintrup, A. ; McFarlane, D. ; Sanchez Lopez, T. ; Owens, K. ; Krechel, W.E.
Page(s): 15 - 32
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6320688

3. Optimization of an Evaluation Function of the Four-Sided Dominos Game Using a Genetic Algorithm
Author(s): Antonio, N.S. ; Costa Filho, C.F.F. ; Costa, M.G.F.
Page(s): 33 - 43
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6327342

4.  Job-Level Proof Number Search
Author(s): Wu, I.-C. ; Lin, H.-H. ; Sun, D.-J. ; Kao, K.-Y. ; Lin, P.-H. ; Chan, Y.-C. ; Chen, P.-T.
Page(s): 44 - 56
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6329938

5. Monte Carlo Tree Search for Collaboration Control of Ghosts in Ms. Pac-Man
Author(s): Nguyen, K.Q. ; Thawonmas, R.
Page(s): 57 - 68
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6307831

6. A Problem Case for UCT
Author(s): Browne, C.
Page(s): 69 - 74
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6310042

Reminder: paper submission deadline for SOCO 2013

A reminder that the deadline for submitting papers to the International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO) 2013 is 20 April 2013. This conference will be held in Salamanca, Spain, 11-13 September, 2013.

IEEE Transactions on Neural Networks and Learning Systems: Volume 24, Issue 4, April 2013

1. Stability Analysis for Neural Networks With Time-Varying Delay Based on Quadratic Convex Combination
Authors: Huaguang Zhang; Feisheng Yang; Xiaodong Liu; Qingling Zhang
Page(s): 513 - 521
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6410434

2. Factor Analysis of Auto-Associative Neural Networks With Application in Speaker Verification
Authors: Sri Garimella; Hynek Hermansky
Page(s): 522 - 528
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6414643

3. Projection-Based Fast Learning Fully Complex-Valued Relaxation Neural Network
Authors: Ramasamy Savitha; Sundaram Suresh; Narasimhan Sundararajan
Page(s): 529 - 541
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6414644

4. Granular Neural Networks: Concepts and Development Schemes
Authors: Mingli Song; Witold Pedrycz
Page(s): 542 - 553
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6415282

5. Noise-Shaping Gradient Descent-Based Online Adaptation Algorithms for Digital Calibration of Analog Circuits
Authors: Shantanu Chakrabartty; Ravi K. Shaga; Kenji Aono
Page(s): 554 - 565
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6416072

6. Cluster Consensus in Discrete-Time Networks of Multiagents With Inter-Cluster Nonidentical Inputs
Authors: Yujuan Han; Wenlian Lu; Tianping Chen
Page(s): 566 - 578
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6418037

7. Common Nature of Learning Between Back-Propagation and Hopfield-Type Neural Networks for Generalized Matrix Inversion With Simplified Models
Authors: Yunong Zhang; Dongsheng Guo; Zhan Li
Page(s): 579 - 592
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6421040

8. Online Support Vector Machine Based on Convex Hull Vertices Selection
Authors: Di Wang; Hong Qiao; Bo Zhang; Min  Wang
Page(s): 593 - 609
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6420961

9. Optimizing Spatial Filters by Minimizing Within-Class Dissimilarities in Electroencephalogram-Based Brain–Computer Interface
Authors: Mahnaz Arvaneh; Cuntai Guan; Kai Keng Ang; Chai Quek
Page(s): 610 - 619
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6423303

10. Just-In-Time Classifiers for Recurrent Concepts
Authors: Cesare Alippi; Giacomo Boracchi; Manuel Roveri
Page(s): 620 - 634
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6425489

11. Least Square Regularized Regression in Sum Space
Authors: Yong-Li Xu; Di-Rong Chen; Han-Xiong Li; Lu Liu
Page(s): 635 - 646
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6425490

12. Dynamic Sampling Approach to Training Neural Networks for Multiclass Imbalance Classification
Authors: Minlong Lin; Ke Tang; Xin  Yao
Page(s): 647 - 660
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6449324

13. New Parameter-Free Simplified Swarm Optimization for Artificial Neural Network Training and its Application in the Prediction of Time Series
Authors: Wei-Chang Yeh
Page(s): 661 - 665
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6410433

14. Distributed Consensus Tracking for Multiple Uncertain Nonlinear Strict-Feedback Systems Under a Directed Graph
Authors: Sung Jin Yoo
Page(s): 666 - 672
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6415283

15. Ensemble Pruning Using Spectral Coefficients
Authors: Terry Windeatt; Cemre Zor
Page(s): 673 - 678
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6423293

Applications of ECoS: First article available online

The first article accepted for my special issue of Evolving Systems on Applications of Kasabov's Evolving Connectionist Systems is now available online. This article is a comprehensive review of the mechanisms and applications of evolving spiking neural networks. I can thoroughly recommend this article to anyone interested in spiking networks. Congratulations to the authors Stefan Schliebs and Nik Kasabov and my thanks to the reviewers for their time and efforts.

On Being a Postdoc 2: Postdoc survival

One of my favourite quotes from the television series Babylon 5 is: "You do not make history, you can only hope to survive it". As it is with history, so it is with being a postdoc. You do not make history as a postdoc, you can only hope to survive being one. I have done three postdocs, one in New Zealand and two in Australia. Now I'm in a permanent academic position, a head of department no less. But I have seen people destroyed by the postdoc system, who have not just lost their jobs but been pushed out of academia completely. Make no mistake, the postdoc process can be brutal, but there are some techniques that I found useful for surviving.

Be nice. While some people seem to think that the ends justify the means, if you mistreat people, eventually you will get a reputation such that no-one wants to work with you. There is no point in being able to attract research funding if you can't find staff to employ with it, and there is no point being a professor in your early thirties if your research group collapses by the time you're forty, thanks to mismanagement of staff. Be nice to people, and they will be nice to you. As my best friend is fond of saying, good things happen to good people. This isn't due to some mystical Karmic process: rather, people will go out of their way to help someone who is nice to them. Loyalty is something that can only be earned, it doesn't magically spring forth from the payment of salary. On the other hand, some people see niceness as weakness and will try to exploit you. Beware of the users!

Be diplomatic. Your supervisor may be egregiously wrong about something, but you don't have to point it out. Far better to subtly lead them to this conclusion, to let them think that they have worked it out by themselves. While it is nice to think that science runs on the free and frank exchange of ideas and opinions, it is in reality a very delicate egosystem. Beware of the toes you step on-they may be connected to a fragile ego and a peevish personality.

Get everything in writing. It never hurts to have written evidence in case everything goes wrong. People break their word, sometimes you need a little bit of evidence to remind them of what they promised.

Write everything down. A career is not built on a single action or accomplishment. Instead, it is built on a long list of actions and accomplishments. If you don't write down everything you do, then you might forget something vital when you go for your next job. In other words, having a comprehensive and up-to-date CV is vital for keeping track of the evidence that shows that you have built a worthwhile career.

Be diverse. Work in different fields and expand your horizons. Each field of research has its own way of doing things, if you work in a different field you will gain fresh perspectives on your own field of study. I spent eight years working in ecology, and what I learned has made me much better at designing experiments in computational intelligence. Beware of staying in a different field for too long: your own field may move on so much that you can't catch up again.

Get involved with professional organisations. For computational intelligence, the best organisation to get involved with is the Institute of Electrical and Electronic Engineers (IEEE), especially the IEEE computational Intelligence Society (CIS). Volunteering for service on committees of professional organisations is a great way to develop your reputation as a competent, hard working professional. It is also a great way of building your network of professional contacts.

Be useful. Work with other people and broaden your network of research collaborators. Help other people out where you can. Not only is this a great way of increasing your publication output, it's also a good way of diversifying your research experience. Collaborating with other researchers can also lead to other research and employment opportunities.

Know when to get out. Sometimes a field is no longer worth pursuing. Sometimes, you have simply gone as high as you can in that field. This is partly why I left ecological modelling, as I'd risen as high as I could without an ecology degree (something I had no interest in acquiring). Sometimes groups get mismanaged to the point that they can't survive, and start losing staff at such a rate that you have no choice but to flee. There is no point being the last person on the Titanic. In other words, don't go down with the ship

Get enough sleep. I have found that every hour of sleep I miss at night costs me two hours of productivity the following day. It is important to sleep during the night: after the sun comes up, the quality of your sleep is cut in half. Missing sleep also depresses your immune system which makes it more likely that you'll get sick. You might miss out on a bit of work time by going to bed early, but how much work time will you miss if you're sick every three weeks?

Work hard. But not too hard. Success comes to those who work the hardest, and in many ways hard work is more important than native ability. But don't work so hard that you miss out on too much sleep. You especially shouldn't work so hard that your family suffers. At the end of they day, your job is just a job, it's not worth sacrificing your quality of life over. You can always catch up on work later, but missed time with your kids is lost forever.

Plan your next move. Within six months of starting a post-doc position you should be planning the move to your next position. This means that you need to have some idea of where you want to go in your career.

You also need to be flexible, you probably won't end up with your dream job, but you probably will end up with a job that is just as good.

Being a postdoc is hard, and really it is best for young, single people. I was thirty-one when I started my first postdoc, and had a brand-new daughter, which made it much harder for me. But I survived, and I'm a better person for it. I hope these strategies are useful for other people.

Conference paper deadline: ICACI 2013

The deadline for submitting papers to the International Conference on Advanced Computational Intelligence (ICACI) 2013 is June 1 2013. This conference will be held in Hangzhou, China, 19-21 October, 2013.

Conference paper deadline: TAAI 2013

The deadline for submitting paper to the Conference on Technologies and Applications of Artificial Intelligence 2013 is 1 August 2013. This conference will be held in Taipei, Taiwan, 6-8 December 2013.