IEEE Transactions on Neural Networks and Learning Systems, Volume 26, Issue 2, February 2015

1. Targeting Accurate Object Extraction From an Image: A Comprehensive Study of Natural Image Matting
Author(s): Qingsong Zhu; Ling Shao; Xuelong Li; Lei Wang
Page(s): 185 - 207

2. Kernel Association for Classification and Prediction: A Survey
Author(s): Yuichi Motai
Page(s): 208 - 223

3. Modified Neural Dynamic Surface Approach to Output Feedback of MIMO Nonlinear Systems
Author(s): Guofa Sun; Dongwu Li; Xuemei Ren
Page(s): 224 - 236

4. Efficient $l_{1}$-Norm-Based Low-Rank Matrix Approximations for Large-Scale Problems Using Alternating Rectified Gradient Method
Author(s): Eunwoo Kim; Minsik Lee; Chong-Ho Choi; Nojun Kwak; Songhwai Oh
Page(s): 237 - 251

5. Semisupervised Feature Selection via Spline Regression for Video Semantic Recognition Constraints
Author(s): Yahong Han; Yi Yang; Yan Yan; Zhigang Ma; Nicu Sebe; Xiaofang Zhou
Page(s): 252 - 264

6. A Scalable Projective Scaling Algorithm for $l_{p}$ Loss With Convex Penalizations
Author(s): Hongbo Zhou; Qiang Cheng
Page(s): 265 - 276

7. Scatter Balance: An Angle-Based Supervised Dimensionality Reduction
Author(s): Shenglan Liu; Lin Feng; Hong Qiao
Page(s): 277 - 289

8. Consensus in Continuous-Time Multiagent Systems Under Discontinuous Nonlinear Protocols
Author(s): Bo Liu; Wenlian Lu; Tianping Chen
Page(s): 290 - 301

9. Backstepping Fuzzy-Neural-Network Control Design for Hybrid Maglev Transportation System
Author(s): Rong-Jong Wai; Jing-Xiang Yao; Jeng-Dao Lee
Page(s): 302 - 317

10. Adaptive Hidden Markov Model With Anomaly States for Price Manipulation Detection
Author(s): Yi Cao; Yuhua Li; Sonya Coleman; Ammar Belatreche; Thomas Martin McGinnity
Page(s): 318 - 330

11. Consensus-Based Distributed Cooperative Learning From Closed-Loop Neural Control Systems
Author(s): Weisheng Chen; Shaoyong Hua; Huaguang Zhang
Page(s): 331 - 345

12. MEC—A Near-Optimal Online Reinforcement Learning Algorithm for Continuous Deterministic Systems
Author(s): Dongbin Zhao; Yuanheng Zhu
Page(s): 346 - 356

13. Passivity of Switched Recurrent Neural Networks With Time-Varying Delays
Author(s): Jie Lian; Jun Wang
Page(s): 357 - 366

14. A Parametric Classification Rule Based on the Exponentially Embedded Family
Author(s): Bo Tang; Haibo He; Quan Ding; Steven Kay
Page(s): 367 - 377

15. VC-Dimension of Univariate Decision Trees
Author(s): Olcay Taner Yildiz
Page(s): 378 - 387

16. Delay-Based Reservoir Computing: Noise Effects in a Combined Analog and Digital Implementation
Author(s): Miguel C. Soriano; Silvia Ortin; Lars Keuninckx; Lennert Appeltant; Jan Danckaert; Luis Pesquera; Guy Van der Sande
Page(s): 388 - 393

17. Non-Divergence of Stochastic Discrete Time Algorithms for PCA Neural Networks
Author(s): Jian Cheng Lv; Zhang Yi; Yunxia Li
Page(s): 394 - 399

18. Asymmetric Mixture Model With Simultaneous Feature Selection and Model Detection
Author(s): Thanh Minh Nguyen; Q. M. Jonathan Wu; Hui Zhang
Page(s): 400 - 408

19. Optimal Codesign of Nonlinear Control Systems Based on a Modified Policy Iteration Method
Author(s): Yu Jiang; Yebin Wang; Scott A. Bortoff; Zhong-Ping Jiang
Page(s): 409 - 414

Neural Networks, Volume 63, Pages 1-292, March 2015

Cognitive Science

A neural network for learning the meaning of objects and words from a featural representation  
Pages: 234-253
Author(s): Mauro Ursino, Cristiano Cuppini, Elisa Magosso

Neuroscience

Circuit design and exponential stabilization of memristive neural networks  
Pages: 48-56
Author(s): Wen, Tingwen Huang, Zhigang Zeng, Yiran Chen, Peng Li

Learning Systems

Performance improvement of classifier fusion for batch samples based on upper integral  
Pages: 87-93
Author(s): Hui-Min Feng, Xi-Zhao Wang

Convex nonnegative matrix factorization with manifold regularization  
Pages: 94-103
Author(s): Wenjun Hu, Kup-Sze Choi, Peiliang Wang, Yunliang Jiang, Shitong Wang

Towards an intelligent framework for multimodal affective data analysis  
Pages: 104-116
Author(s): Soujanya Poria, Erik Cambria, Amir Hussain, Guang-Bin Huang

Approximate kernel competitive learning  
Pages: 117-132
Author(s): Jian-Sheng Wu, Wei-Shi Zheng, Jian-Huang Lai

A vector reconstruction based clustering algorithm particularly for large-scale text collection  
Pages: 141-155
Author(s): Ming Liu, Chong Wu, Lei Chen

Active learning for semi-supervised clustering based on locally linear propagation reconstruction  
Pages: 170-184
Author(s): Chin-Chun Chang, Po-Yi Lin

Adaptive learning rate of SpikeProp based on weight convergence analysis  
Pages: 185-198
Author(s): Sumit Bam Shrestha, Qing Song

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise  
Pages: 199-207
Author(s): Randa Herzallah

Self-organizing maps based on limit cycle attractors  
Pages: 208-222
Author(s): Di-Wei Huang, Rodolphe J. Gentili, James A. Reggia

Mathematical and Computational Analysis

Projective synchronization of fractional-order memristor-based neural networks  
Pages: 1-9
Author(s): Hai-Bo Bao, Jin-De Cao

Estimates on compressed neural networks regression  
Pages: 10-17
Author(s): Yongquan Zhang, Youmei Li, Jianyong Sun, Jiabing Ji

Global exponential stability of delayed Markovian jump fuzzy cellular neural networks with generally incomplete transition probability  
Pages: 18-30
Author(s): Yonggui Kao, Lei Shi, Jing Xie, Hamid Reza Karimi

Jackson-type inequalities for spherical neural networks with doubling weights  
Pages: 57-65
Author(s): Shaobo Lin, Jinshan Zeng, Lin Xu, Zongben Xu

RBF-network based sparse signal recovery algorithm for compressed sensing reconstruction  
Pages: 66-78
Author(s): Vidya L., Vivekanand V., Shyamkumar U., Deepak Mishra

Finite-time synchronization control of a class of memristor-based recurrent neural networks  
Pages: 133-140
Author(s): Minghui Jiang, Shuangtao Wang, Jun Mei, Yanjun Shen

Dynamics of neural networks over undirected graphs  
Pages: 156-169
Author(s): Eric Goles, Gonzalo A. Ruz

Convergence and attractivity of memristor-based cellular neural networks with time delays  
Pages: 223-233
Author(s): Sitian Qin, Jun Wang, Xiaoping Xue

Massively parallel neural circuits for stereoscopic color vision: Encoding, decoding and identification  
Pages: 254-271
Author(s): Aurel A. Lazar, Yevgeniy B. Slutskiy, Yiyin Zhou

Neural network for constrained nonsmooth optimization using Tikhonov regularization  
Pages: 272-281
Author(s): Sitian Qin, Dejun Fan, Guangxi Wu, Lijun Zhao

Engineering and Applications

Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise  
Pages: 31-47
Author(s): Najdan Vuković, Zoran Miljković

Fast Clustered Radial Basis Function Network as an adaptive predictive controller  
Pages: 79-86
Author(s): Dino Kosic

Designing a deep brain stimulator to suppress pathological neuronal synchrony  
Pages: 282-292
Author(s): Ghazal Montaseri, Mohammad Javad Yazdanpanah, Fariba Bahrami

IEEE Transactions on Evolutionary Computation, Volume 19, Number 1, February 2015

1. Adaptive Multiobjective Particle Swarm Optimization Based on Parallel Cell Coordinate System
Author(s): Hu, W. ; Yen, G.G.
Page(s): 1 - 18

2. Characterization of the Performance of Memetic Algorithms for the Automation of Bone Tracking With Fluoroscopy
Author(s): Tersi, L. ; Fantozzi, S. ; Stagni, R.
Page(s): 19 - 30

3. Enhancing Differential Evolution Utilizing Eigenvector-Based Crossover Operator
Author(s): Guo, S. ; Yang, C.
Page(s): 31 - 49

4. A New Local Search-Based Multiobjective Optimization Algorithm
Author(s): Chen, B. ; Zeng, W. ; Lin, Y. ; Zhang, D.
Page(s): 50 - 73

5. Exploratory Landscape Analysis of Continuous Space Optimization Problems Using Information Content
Author(s): Munoz, M.A. ; Kirley, M. ; Halgamuge, S.K.
Page(s): 74 - 87

6. Learning Value Functions in Interactive Evolutionary Multiobjective Optimization
Author(s): Branke, J. ; Greco, S. ; Slowinski, R. ; Zielniewicz, P.
Page(s): 88 - 102

7. The Rolling Tide Evolutionary Algorithm: A Multiobjective Optimizer for Noisy Optimization Problems
Author(s): Fieldsend, J.E. ; Everson, R.M.
Page(s): 103 - 117

8. Optimizing Existing Software With Genetic Programming
Author(s): Langdon, W.B. ; Harman, M.
Page(s): 118 - 135

9. History-Based Topological Speciation for Multimodal Optimization
Author(s): Li, L. ; Tang, K.
Page(s): 136 - 150

10. Intelligent Bandwidth Estimation for Variable Bit Rate Traffic
Author(s): Khan, G.M. ; Arshad, R. ; Mahmud, S.A. ; Ullah, F.
Page(s): 151 - 155

CFP: IEEE CIM special issue on "Computational Intelligence for Brain Computer Interfaces"

IEEE Computational Intelligence Magazine Special Issue on Computational Intelligence for Brain Computer Interfaces
http://www.husseinabbass.net/ieeecimbci2016.html
Hussein A. Abbass, Cuntai Guan, Kay Chen Tan

Aims and Scope

Brain Computer Interfaces (BCI) aims at establishing a one or two-way communication protocol between the human brain and an electronic device. The research umbrella of BCI has different names and overlaps with different research areas that evolved under the wider objective of connecting human data to an electronic device of some sort. Some of these areas include: adaptive automation, augmented cognition, brain-machine interface, human-machine symbiosis, and human-computer symbiosis.

The last decade has witnessed a rise in the number of researchers working on BCI. With the advances of sensor technologies, efficient signal processing algorithms, and parallel computing, it was possible to finally realize the dream of many researchers who talked about the concept in one form or another in the sixties and seventies including J.C.R. Licklider, R.B. Rouse, and others. Different sensor and measurement technologies are evolving rapidly from the classical functional magnetic resonance imaging (fMRI), functional near infrared (fNIR), Electroencephalography (EEG), to complex integrated psycho-physiological sensor arrays.

Researchers in Computational Intelligence have been better situated than ever to extract knowledge from these signals, transform it to actionable decisions, and designing the intelligent machine that has long been promised and is now overdue. Success has been seen in many medical applications including assisting people on wheelchairs, stroke rehabilitation, and epileptic seizures. In the non-medical domain, BCI has been used for computer games, authentication in cyber security, and air traffic control.

This special issue aims at showcasing the most exciting and recent advances in BCI and related topics. The guest editors invite submissions of previously unpublished, recent and exciting research on BCI. The special issue welcomes survey, position, and research papers

Topics of Interest

• Adaptive control schemes for BCI
• Applications
• Augmented cognition and adaptive aiding using BCI
• Big data for brain mining
• Collaborative multi-humans BCI environments
• Computational intelligence applications for BCI
• Data and signal processing techniques for BCI applications
• Evolutionary algorithms for BCI
• Fusion of heterogeneous psycho-physiological sensors
• Fuzzy logic for BCI
• Neuroplasticity induced by brain-computer interactions
• Neural networks for BCI
• Novel sensor technologies for BCI
• Related computational intelligence methods for BCI
• Situation awareness systems for BCI applications
• Swarm techniques for BCI
• Other closely related topics on computational intelligence for BCI

Submission Process

The maximum length for the manuscript is typically 25 pages in single column format with double-spacing, including figures and references. Authors should specify on the first page of their manuscripts the corresponding author’s contact and up to 5 keywords. Submission should be made via https://www.easychair.org/conferences/?conf=ieeecimbci2016

Important Dates

15th May, 2015: Submission of Manuscripts
15th July, 2015: Notification of Review Results
15th August, 2015: Submission of Revised Manuscripts
15th September, 2015: Submission of Final Manuscripts
February 2016: Special Issue Publication

Guest Editors

Professor Hussein Abbass
University of New South Wales
Canberra, Northcott Drive, ACT 2600, Australia
Email: h.abbass@adfa.edu.au

Professor Cuntai Guan
Institute for Infocomm Research (I2R),
1 Fusionopolis Way, Fusionopolis, Singapore 138632
Email: ctguan@i2r.a-star.edu.sg

Professor Kay Chen Tan
National University of Singapore
4 Engineering Drive, Singapore 117583
Email: eletankc@nus.edu.sg

CFP: Evolutionary Computation Journal (MIT Press) special issue on "Combinatorial Optimization Problems"

Special Issue in Evolutionary Computation Journal, MIT Press, on Combinatorial Optimization Problems

DESCRIPTION

Combinatorial Optimization Problems consist in finding an optimal solution (according to some objective function) from a finite search space. These problems arise in Industry and Academia and, unfortunately, most of them cannot be solved efficiently, that is, they are NP-hard and no polynomial time algorithm is known to solve them. For this reason, in the last decades researches have investigated the use of stochastic search algorithms to find near optimal solutions to these problems. In particular, a great research effort has been devoted to the development of metaheuristic algorithms to solve combinatorial optimization problems.

Successfully solved problems include scheduling, timetabling, network design, transportation and distribution problems, vehicle routing, travelling salesman, graph problems, satisfiability, energy optimization problems, packing problems and planning problems.

Prominent examples of metaheuristics include evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, ant colony optimization, particle swarm optimization, variable neighbourhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms, hyperheuristics and hybrid algorithms.

We encourage authors to submit original high-quality research on the application of metaheuristic algorithms to combinatorial optimization problems or theoretical aspects of this application.

SUBMISSION GUIDELINES

All submissions have to be prepared according to the "guidelines for authors" as published in the journal website at http://ecj.fhv.at. Authors should submit their manuscripts to the Evolutionary Computation Editorial Manager at http://ecj.fhv.at . When submitting a paper, please send at the same time an email to Francisco Chicano (chicano@lcc.uma.es) and a copy to ecj@fhv.at mentioning the special issue, the paper title, and author list to inform about the submission.

TENTATIVE SCHEDULE

15 August 2015       submission deadline
15 December 2015     authors notification
15 March 2016        authors’ revisions
1 July 2016          final notification
15 July 2016         final manuscript
Winter 2016          tentative publication

GUEST EDITORS

Francisco Chicano
e-mail: chicano@lcc.uma.es
University of Malaga, Spain

Christian Blum
e-mail: christian.blum@ehu.es
University of the Basque Country, Spain

Gabriela Ochoa
e-mail: gabriela.ochoa@cs.stir.ac.uk
University of Stirling, Scotland, UK

CFP: IEEE TFS Special Issue on "Fuzzy Techniques in Financial Modelling and Simulation"

I. AIMS AND SCOPE

Computational intelligence has attracted a significant and increasing interest from the financial engineering and economics communities in recent years.  Computational systems capturing sentiments, preferences, behaviour and beliefs, are becoming indispensable in virtually all financial applications, from portfolio selection to proprietary trading, algorithmic trading, and risk management.  The bar has been raised with the revision of regulations, and the required compliance and risk management.  The new rules should be implemented through new processes and supported by developing new computational tools.

The fuzzy systems domain provides an armoury of techniques to address the challenges currently encountered in the financial engineering area.  Fuzzy logic can be used to effectively describe and incorporate financial experts’ and market participants’ intuition and behaviour, reaching beyond the capabilities of probabilistic models traditionally used in financial modelling.  In addition, fuzzy techniques can be used in conjunction with probabilistic models or with other machine learning techniques, such as evolutionary optimisation methods or neural networks, in order to better address the challenges raised in this area.

The objective of this special issue is to bring together the most recent advances in the design and application of fuzzy approaches to real problems in financial engineering.  A focus of interest is simulating scenarios at different level of granularity, as well as developing test environments for new financial and banking regulation, while accommodating behavioural aspects.

II. TOPICS COVERED

This special issue solicits original contributions on theoretical developments for financial modelling and simulations based on the following paradigms:

• fuzzy time series         
• fuzzy data mining
• fuzzy intelligent          
• fuzzy optimisation
• decision-making           
• fuzzy systems
• fuzzy granular             
• fuzzy-rough approaches
• computing                   
• evolving fuzzy systems
• neuro-fuzzy systems     
• support vector machines

Application papers of these paradigms to the following financial engineering areas are welcome:

• agent-based artificial financial markets
• financial-regulation test environments
• financial sentiment analysis, emotion mining
• financial scenarios modelling and simulation
• algorithmic trading       
• instruments pricing
• financial forecasting     
• risk management
• contagion analysis        
• systemic risk modelling
• portfolio optimization   
• trading strategies
• behavioural finance      
• finance big data analytics

III. IMPORTANT DATES

July 1, 2015: Submission deadline
Oct. 1, 2015: Notification of the first-round review
Nov. 1, 2015: Revised submission due
Dec. 15, 2015: Final notice of acceptance/reject

IV. SUBMISSION GUIDELINES

Manuscripts should be prepared according to the instruction of the “Information for Authors” section of the journal found and submission should be done through the IEEE TFS journal website: http://mc.manuscriptcentral.com/tfs-ieee Clearly mark “Special Issue on Fuzzy Techniques in Financial Modelling and Simulation” in your cover letter to the Editor-in-Chief. All submitted manuscripts will be reviewed using the standard procedure that is followed for regular submissions.

V. GUEST EDITORS

Ronald Yager
Machine Intelligence Institute
Iona College, USA
ryager@iona.edu

Antoaneta Serguieva
Financial Computing and Analytics Group
University College London, UK
a.serguieva@ucl.ac.uk

Vasile Palade
Faculty of Engineering and Computing
Coventry University, UK
vasile.palade@coventry.ac.uk

Hisao Ishibuchi
Computer Science and Intelligent Systems
Osaka Prefecture University, Japan
hisaoi@cs.osakafu-u.ac.jp

Neural Networks, Volume 62, Pages 1-118, February 2015

Communication and Brain  
Author(s): Yutaka Sakaguchi, Takeshi Aihara, Peter Ford Dominey, Ichiro Tsuda
Pages: 1-2

Mathematical Theory and Model

Mathematical modeling for evolution of heterogeneous modules in the brain  
Author(s): Yutaka Yamaguti, Ichiro Tsuda
Pages: 3-10

Self-organization of a recurrent network under ongoing synaptic plasticity  
Author(s): Takaaki Aoki
Pages: 11-19

Hodge–Kodaira decomposition of evolving neural networks  
Author(s): Keiji Miura, Takaaki Aoki
Pages: 20-24

Memories as bifurcations: Realization by collective dynamics of spiking neurons under stochastic inputs
Author(s): Tomoki Kurikawa, Kunihiko Kaneko
Pages: 25-31

Multistate network model for the pathfinding problem with a self-recovery property
Author(s): Kei-Ichi Ueda, Masaaki Yadome, Yasumasa Nishiura
Pages: 32-38

Neural coordination can be enhanced by occasional interruption of normal firing patterns: A self-optimizing spiking neural network model  
Author(s): Alexander Woodward, Tom Froese, Takashi Ikegami
Pages: 39-46

Physiology, Neuroscience and Model

Phase shifts in alpha-frequency rhythm detected in electroencephalograms influence reaction time  
Author(s): Yasushi Naruse, Ken Takiyama, Masato Okada, Hiroaki Umehara, Yutaka Sakaguchi
Pages: 47-51

Spatial consistency of neural firing regulates long-range local field potential synchronization: A computational study  
Author(s): Naoyuki Sato
Pages: 52-61

Arm-use dependent lateralization of gamma and beta oscillations in primate medial motor areas  
Author(s): Ryosuke Hosaka, Toshi Nakajima, Kazuyuki Aihara, Yoko Yamaguchi, Hajime Mushiake
Pages: 62-66

Spatiotemporal patterns of current source density in the prefrontal cortex of a behaving monkey  
Author(s): Kazuhiro Sakamoto, Norihiko Kawaguchi, Kohei Yagi, Hajime Mushiake
Pages: 67-72

Computational model of visual hallucination in dementia with Lewy bodies  
Author(s): Hiromichi Tsukada, Hiroshi Fujii, Kazuyuki Aihara, Ichiro Tsuda
Pages: 73-82

Behavioral and System model

Immediate return preference emerged from a synaptic learning rule for return maximization  
Author(s): Yoshiya Yamaguchi, Takeshi Aihara, Yutaka Sakai
Pages: 83-90

A wavelet-based method for extracting intermittent discontinuities observed in human motor behavior  
Author(s): Yasuyuki Inoue, Yutaka Sakaguchi
Pages: 91-101

Exploiting the gain-modulation mechanism in parieto-motor neurons: Application to visuomotor transformations and embodied simulation  
Author(s): Sylvain Mahé, Raphaël Braud, Philippe Gaussier, Mathias Quoy, Alexandre Pitti
Pages: 102-111

Communication, concepts and grounding  
Author(s): Frank van der Velde
Pages: 112-117

Call for Papers: IEEE 2015 International Conference on Data Science and Advanced Analytics

Preliminary Call for Papers: IEEE 2015 International Conference on Data Science and Advanced Analytics (DSAA 2015)

19-21 October, 2015, Paris, France

Website: http://dsaa2015.lip6.fr/

Important Dates

Paper Submission deadline: 18 May, 2015
Notification of acceptance: 6 July, 2015
Final Camera-ready papers due: 28 August, 2015

Publications

All accepted papers will be published by IEEE and included in the IEEE Xplore Digital Library. The conference proceedings will be submitted for EI indexing through INSPEC by IEEE. Top quality papers accepted and presented at the conference will be selected for extension and publication in the special issues of some international journals, including IEEE Intelligent Systems and WWWJ.

Introduction

Data driven scientific discovery is an important emerging paradigm for computing in areas including social, service, Internet of Things, sensor networks, telecommunications, biology, health-care and cloud. Under this paradigm, Data Science is the core that drives new researches in many areas, from environmental to social. There are many associated scientific challenges, ranging from data capture, creation, storage, search, sharing, modeling, analysis, and visualization. Among the complex aspects to be addressed we mention here the integration across heterogeneous, interdependent complex data resources for real-time decision making, streaming data, collaboration, and ultimately value co-creation. Data science encompasses the areas of data analytics, machine learning, statistics, optimization and managing big data, and has become essential to glean understanding from large data sets and convert data into actionable intelligence, be it data available to enterprises, Government or on the Web.

Following the first successful edition held in 2014 in Shanghai, the 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA 2015) aims to provide a premier forum that brings together researchers, industry practitioners, as well as potential users of big data, for discussion and exchange of ideas on the latest theoretical developments in Data Science as well as on the best practices for a wide range of applications.

DSAA is also technically sponsored by ACM through SIGKDD.

DSAA'2015 will consist of two main Tracks: Research and Application; the Research Track is aimed at collecting contributions related to theoretical foundations of Data Science and Data Analytics. The Application Track is aimed at collecting contributions related to applications of Data Science and Data Analytics in real life scenarios. DSAA solicits then both theoretical and practical works on data science and advanced analytics.

Topics of Interest

General areas of interest to DSAA'2015 include but are not limited to:
1. Foundations

• New mathematical, probabilistic and statistical models and theories
• New machine learning theories, models and systems
• New knowledge discovery theories, models and systems
• Manifold and metric learning, deep learning
• Scalable analysis and learning
• Non-iidness learning
• Heterogeneous data/information integration
• Data pre-processing, sampling and reduction
• High dimensional data, feature selection and feature transformation
• Large scale optimization
• High performance computing for data analytics
• Architecture, management and process for data science

2. Data analytics, machine learning and knowledge discovery

• Learning for streaming data
• Learning for structured and relational data
• Intent and insight learning
• Mining multi-source and mixed-source information
• Mixed-type and structure data analytics
• Cross-media data analytics
• Big data visualization, modeling and analytics
• Multimedia/stream/text/visual analytics
• Relation, coupling, link and graph mining
• Personalization analytics and learning
• Web/online/social/network mining and learning
• Structure/group/community/network mining
• Cloud computing and service data analysis

3. Storage, retrieval and search

• Data warehouses, cloud architectures
• Large-scale databases
• Information and knowledge retrieval
• Information and knowledge retrieval
• Web/social/databases query and search
• Personalized search and recommendation
• Human-machine interaction and interfaces
• Crowdsourcing and collective intelligence

4. Privacy and security

• Security, trust and risk in big data
• Data integrity, matching and sharing
• Privacy and protection standards and policies
• Privacy preserving big data access/analytics
• Social impact

5. Applications, practices, tools and evaluation

• Best practices and lessons
• Data-intensive organizations, business and economy
• Domain-specific applications
• Business/government analytics
• Online/social/living/environment data analysis
• Mobile analytics for hand-held devices
• Quality assessment and interestingness metrics
• Complexity, efficiency and scalability
• Anomaly/fraud/exception/change/event/crisis analysis
• Large-scale recommender and search systems
• Big data representation and visualization
• Large scale application case studies

Organizing Committee

Honorary Chair
Usama Fayyad, Barclays Bank, UK

General Chairs
Longbing Cao, University of Technology Sydney, Australia
Eric Gaussier, University Joseph Fourier, France

Conference Chairs
Olivier Capp, Telecom Paristech, CNRS, France
Wei Wang, University of California at Los Angeles, USA

Research Track Chairs
Patrick Gallinari, University Pierre & Marie Curie, France
James Kwok, Hong Kong University of Science and Technology, China

Application Track Chairs
Gabriella Pasi, Universita degli Studi di Milano Biccoca, Italy
Osmar Zaiane, Univ. of Alberta, Canada

Call for Papers: 12th International Symposium on Neural Networks (ISNN2015)

Call for papers: 12th International Symposium on Neural Networks (ISNN2015)， October 15-18, 2015, Jeju, Korea

Sponsors and co-sponsor: The Chinese University of Hong Kong, Pusan National University

Technical co-sponsors: Asia Pacific Neural Network Assembly (pending), IEEE Computational Intelligence Society (pending), International Neural Network Society, and Korean Institute of Intelligent Systems

Website: http://isnn.mae.cuhk.edu.hk

Important Dates

Special session proposals deadline April 15, 2015
Paper submission deadline May 15, 2015
Notification of acceptance June 15, 2015
Camera-ready copy and author registration July 15, 2015

Following the successes of previous events, Twelfth International Symposium on Neural Networks (ISNN 2015) will be held in Jeju, Korea. Jeju's temperate climate, natural scenery, and beaches make it a popular tourist destination for South Koreans as well as visitors from other parts of East Asia. There are numerous popular tourist spots on the island, such as Cheonjeyeon Waterfalls, Mount Halla, Hyeobje Cave, and Hyeongje Island. In particular, Jeju Volcanic Island and Lava Tubes was listed by UNESCO as a World Natural Heritage. ISNN 2015 aims to provide a high-level international forum for scientists, engineers, and educators to present the state of the art of neural network research and applications in related fields. The symposium will feature plenary speeches given by world renowned scholars, regular sessions with broad coverage, and special sessions focusing on popular topics.

Call for Papers and Special Sessions

Prospective authors are invited to contribute high-quality papers to ISNN 2015. In addition, proposals for special sessions within the technical scopes of the symposium are solicited. Special sessions, to be organized by internationally recognized experts, aim to bring together researchers in special focused topics. Papers submitted for special sessions are to be peer-reviewed with the same criteria used for the contributed papers. Researchers interested in organizing special sessions are invited to submit formal proposals to ISNN 2015. A special session proposal should include the session title, a brief description of the scope and motivation, names, contact information and brief biographical information of the organizers.

Topic Areas

Topics areas include, but not limited to, computational neuroscience, connectionist theory and cognitive science, mathematical modeling of neural systems, neurodynamic analysis, neurodynamic optimization and adaptive dynamic programming, embedded neural systems, probabilistic and information-theoretic methods, principal and independent component analysis, hybrid intelligent systems, supervised, unsupervised, and reinforcement learning, deep learning, brain imaging and neural information processing, neuroinformatics and bioinformatics, support vector machines and kernel methods, autonomous mental development, data mining, pattern recognition, time series analysis, image and signal processing, robotic and control applications, telecommunications, transportation systems, intrusion detection and fault diagnosis, hardware implementation, real-world applications.

Paper Submission

Authors are invited to submit full-length papers (10 pages maximum) by the submission deadline through the online submission system. Potential organizers are also invited to enlist five or more papers with cohesive topics to form special sessions. The submission of a paper implies that the paper is original and has not been submitted under review or is not copyright-protected elsewhere and will be presented by an author if accepted. All submitted papers will be refereed by experts in the field based on the criteria of originality, significance, quality, and clarity. The authors of accepted papers will have an opportunity to revise their papers and take consideration of the referees' comments and suggestions. Papers presented at ISNN 2015 will be published in the EI-indexed proceedings in the Springer LNCS series and selected good papers will be included in special issues of several SCI journals.

Organizers:

General Chair
Jun Wang, The Chinese University of Hong Kong, Hong Kong

Steering Chair
Derong Liu, Chinese Academy of Sciences, Beijing, China and University of Illinois - Chicago, USA

Organizing Committee Chairs
Chengan Guo, Dalian University of Technology, Dalian, China
Sungshin Kim, Pusan National University, Busan, Korea
Zhigang Zeng, Huazhong University of Science and Technology, Wuhan, China

Program Chairs
Xiaolin Hu, Tsinghua University, Beijing, China
Yousheng Xia, Fuzhou University, Fuzhou, China
Yunong Zhang, Sun Yet-sen University, Guangzhou, China
Dongbin Zhao, Institute of Automation, Chinese Academy of Sciences, Beijing, China

Special Sessions Chairs
Sanqing Hu, Hangzhou Dianzi University, Hangzhou, China
Kwang Baek Kim, Silla University, Busan, Korea
Tieshan Li, Dalian Maritime University, Dalian, China

Publicity Chairs
Yuanqing Li, South China University of Technology, Guangzhou, China
Yi Shen, Huazhong University of Science and Technology, Wuhan, China
Zhang Yi, Sichuan University, Chengdu, China

Publications Chairs
Jianchao Fan, National Marine Environmental Monitoring Center, Dalian, China
Jin Hu, Chongqing Jiaotong University, Chongqing, China
Zheng Yan, Huawei Shannon Laboratory, Beijing, China

Registration Chairs
Shenshen Gu, Shanghai University, Shanghai, China
Qingshan Liu, Huazhong University of Science and Technology, Wuhan, China

Secretariat
Xinyi Le, The Chinese University of Hong Kong, Hong Kong

Webmaster
Shaofu Yang, The Chinese University of Hong Kong, Hong Kong

CFP: IEEE TNNLS special issue on "New Developments in Neural Network Structures for Signal Processing, Autonomous Decision, and Adaptive Control"

There has been continuously increasing interest in applying neural networks to identification and adaptive control of practical systems that are characterized by nonlinearity, uncertainty, communication constraints, and complexity. The past few years have witnessed a variety of new developments in neural-network-based approaches for behavior learning, information processing, autonomous decision, and system control. Biologically inspired neural network structures can significantly enhance the capabilities of information processing, control and computational performance. New discoveries in neurocognitive psychology, sociology, and elsewhere reveal new neurological learning structures with more powerful capabilities in complex problem solving and fast decision in dynamic environments.  The goal of the special issue is to consolidate recent new developments in neural network structures for signal processing, autonomous decision, and adaptive control with application to complex systems. It welcomes contributions from a wide range of research aspects relevant to the topic, including neural computing, adaptive control, cooperative control, autonomous decision systems, mathematical and computational models, neuropsychology decision and control, algorithms, simulation, applications and/or case studies.

SCOPE OF THE SPECIAL ISSUE

We invite original contributions related to new neural network structures and methods, adaptive neural network control, from theories, algorithms, modelling to experimental studies and applications. Topics include but are not limited to:

• Bio-inspired neural network structures for signal processing
• Cognitive computing and intelligent control
• Fast satisficing decision & control based on risk, gist and environmental cues
• Cooperative control using neural network structures
• Brain-like control design and applications
• New neural network topologies from neurocognitive psychology studies
• Neurocomputing structures for fast decision and control in dynamic environments
• Neural-adaptive learning in distributed multi-agent systems
• Spike timing-based learning algorithms with hierarchical/complex architectures
• Autonomous decision and control using neural structures
• Memory-based reasoning, prediction and control

Important Dates

31 Mar 2015 – Deadline for manuscript submission
31 May 2015 – Notification of authors
31 June 2015 – Deadline for submission of revised manuscripts
31 July 2015 – Final decision of acceptance
Nov. 2015 – Tentative Publication Date

Guest Editors

• Y.D. Song, Chongqing University, China, ydsong@cqu.edu.cn 
• F.L. Lewis, University of Texas at Arlington, USA
• Marios Polycarpou, University of Cyprus
• Danil Prokhorov, Toyota Research Institute North America, Ann Arbor, MI.
• Dongbin Zhao, Institute of Automation, Chinese Academy of Sciences, Beijing

Submission Instructions

1. Read the information for Authors at http://cis.ieee.org/tnnls
2. Submit your manuscript by 31 March 2015 at the TNNLS webpage (http://mc.manuscriptcentral.com/tnnls) and follow the submission procedure. Please, clearly indicate on the first page of the manuscript and in the cover letter that the manuscript has been submitted to the special issue on New Developments in Neural Network Structures for Signal Processing, Autonomous Decision, and Adaptive Control . Send also an email to guest editor Y.D. Song with subject “TNNLS special issue submission” to notify about your submission.

Call For Papers: IEEE CIM special issue on "Computational Intelligence for Changing Environments"

IEEE Computational Intelligence Magazine Special Issue on Computational Intelligence for Changing Environments
Amir Hussain, Dacheng Tao, Jonathan Wu and Dongbin Zhao

Aims and Scope:

Over the past decade or so, computational intelligence techniques have been highly successful for solving big data challenges in changing environments. In particular, there has been growing interest in so called biologically inspired learning (BIL), which refers to a wide range of learning techniques, motivated by biology, that try to mimic specific biological functions or behaviors. Examples include the hierarchy of the brain neocortex and neural circuits, which have resulted in biologically-inspired features for encoding, deep neural networks for classification, and spiking neural networks for general modelling.

To ensure that these models are generalizable to unseen data, it is common to assume that the training and test data are independently sampled from an identical distribution, known as the sample i.i.d. assumption. In dynamic and non-stationary environments, the distribution of data changes over time, resulting in the phenomenon of ‘concept drift’ (also known as population drift or concept shift), which is a generalization of covariance shift in statistics. Over the last five years, transfer learning and multitask learning have been used to tackle this problem. Fundamental analyses using probably approximately correct (PAC) and Rademacher complexity frameworks have explained why appropriate incorporation of context and concept drift can improve generalizability in changing environments.

It is possible to use human-level processing power to tackle concept drift in changing enviroments. Concept drift is a real-world problem, usually associated with online and concept learning, where the relationships between input data and target variables dynamically change over time. Traditional learning schemes do not adequately address this issue, either because they are offline or because they avoid dynamic learning. However, BIL seems to possess properties that would be helpful for solving concept drift problems in changing environments. Intuitively, the human capacity to deal with concept drift is innate to cognitive processes, and the learning problems susceptible to concept drift seem to share some of the dynamic demands placed on plastic neural areas in the brain. Using improved biological models in neural networks can provide insight into cognitive computational phenomena.

However, a main outstanding issue in using computational intelligence for changing enviroments and domain adaptation is how to build complex networks, or how networks should be connected to the features, samples, and distribution drifts. Manual design and building of these networks are beyond current human capabilities. Recently, computational intelligence methods has been used to address concept drift in changing enviroments, with promising results. A Hebbian learning model has been used to handle random, as well as correlated, concept drift. Neural networks have been used for concept drift detection, and the influence of latent variables on concept drift in a neural network has been studied. In another study, a timing-dependent synapse model has been applied to concept drift. These works mainly apply biologically-plausible computational models to concept drift problems. Although these results are still in their infancy, they open up new possibilities to achieve brain-like intelligence for solving concept drift problems in changing environments.

Taking the current state of research in computational intelligence for changing environments into account, the objective of this special issue is to collate this research to help unify the concepts and terminology of computational intelligence in changing environments, and to survey state-of-the-art computational intelligence methodologies and the key techniques investigated to date. Therefore, this special issue invites submissions on the most recent developments in computational intelligence for changing enviroments algorithms and architectures, theoretical foundations, and representations, and their application to real-world problems. We also welcome timely surveys and review papers.

Topics of Interest include (but are not limited to):

• Computational intelligence methodologies and implementation for changing environments
• Transfer learning
• Multitask learning
• Domain adaption
• Incremental Learning architectures
• Incremental Unsupervised and semi-supervised learning architectures
• Incremental Incremental Representation learning and disentangling
• Incremental Knowledge augmentation
• Incremental Adaptive Neuro-fuzzy systems
• Incremental and single-pass data mining
• Incremental Neural Clustering
• Incremental Neural regression
• Incremental Adaptive decision systems
• Incremental Feature selection and reduction
• Incremental Constructive Learning
• Novelty detection in Incremental learning

Submission Process

The maximum length for the manuscript is typically 25 pages in single column format with double-spacing, including figures and references. Authors should specify in the first page of their manuscripts the corresponding author’s contact and up to 5 keywords. Submission should be made via:

https://www.easychair.org/conferences/?conf=ieeecimcdbil2015.

Important Dates

1st Feb, 2015: Submission of Manuscripts
15th April, 2015: Notification of Review Results
15th May, 2015: Submission of Revised Manuscripts
15th June, 2015: Submission of Final Manuscripts
November 2015: Publication

Guest Editor

Professor Amir Hussain
University of Stirling
Stirling FK9 4LA SCOTLAND, UK
Email: ahu@cs.stir.ac.uk

Professor Dacheng Tao
University of Technology, Sydney
235 Jones Street, Ultimo, NSW 2007, Australia
Email: dacheng.tao@uts.edu.au

Professor Jonathan Wu
University of Windsor
401 Sunset Avenue, Windsor, ON, Canada
Email: jwu@uwindsor.ca

Professor Dongbin Zhao
Institute of Automation, Chinese Academy of Sciences,
No. 95, Zhongguancun East Road, Beijing 100190, China
E-mail: dongbin.zhao@gmail.com

IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games: Volume 6, Number 4, December 2014

1. Guest Editorial: General Games
Author(s): Browne, C. ; Togelius, J. ; Sturtevant, N.
Page(s): 317 - 319

2. The Game Description Language Is Turing Complete
Author(s): Saffidine, A.
Page(s): 320 - 324
A
3. An Extensible Description Language for Video Games
Author(s): Schaul, T.
Page(s): 325 - 331

4. The Axiom General Purpose Game Playing System
Author(s): Schmidt, G.
Page(s): 332 - 342

5. Efficiency of GDL Reasoners
Author(s): Schiffel, S. ; Bjornsson, Y.
Page(s): 343 - 354

6. A Neuroevolution Approach to General Atari Game Playing
Author(s): Hausknecht, M. ; Lehman, J. ; Miikkulainen, R. ; Stone, P.
Page(s): 355 - 366

7. Self-Adaptation of Playing Strategies in General Game Playing
Author(s): Swiechowski, M. ; Mandziuk, J.
Page(s): 367 - 381

8. EvoMCTS: A Scalable Approach for General Game Learning
Author(s): Benbassat, A. ; Sipper, M.
Page(s): 382 - 394

9. Decaying Simulation Strategies
Author(s): Tak, M.J.W. ; Winands, M.H.M. ; Bjornsson, Y.
Page(s): 395 - 406

10. 2015 IEEE conference on computational intelligence and games
Page(s): 407

IEEE Transactions on Autonomous Mental Development: Volume 6, Number 4, December 2014

1. Editorial: Renewal for the IEEE Transactions on Autonomous Mental Development
Author(s): Z. Zhang
Pages: 241-242

2. The Fourth IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EpiRob)2014: Conference Summary and Report
Author(s): G. Metta, L. Natale, and M. Lee
Pages: 243
a
3. Learning from Demonstration in Robots using the Shared Circuits Model
Author(s): K. M. U. Suleman and M. M. Awais
Pages: 244-258

4. A Hierarchical System for a Distributed Representation of the Peripersonal Space of a Humanoid Robot
Author(s): M. Antonelli, A. Gibaldi, F. Beuth, A. J. Duran, A. Canessa, M. Chessa, F. Solari, A. P. del Pobil, F. Hamker, E. Chinellato, and S. P. Sabatini
Pages: 259-273

5. A Wearable Camera Detects Gaze Peculiarities during Social Interactions in Young Children with PervasiveDevelopmental Disorders
Author(s): S. Magrelli, B. Noris, P. Jermann, F. Ansermet, F. Hentsch, J. Nadel, and A. G. Billard
Pages: 274-285

6. Optimal Rewards for Cooperative Agents
Author(s): B. Liu, S. Singh, R. L. Lewis, and S. Qin
Pages: 286-297

IEEE Transactions on Neural Networks and Learning Systems: Volume 26, Issue 1, January 2015

1. Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part I)
Author(s): Xia Liu; Shaobo Lin; Jian Fang; Zongben Xu
Page(s): 7 - 20

2. Is Extreme Learning Machine Feasible? A Theoretical Assessment (Part II)
Author(s): Shaobo Lin; Xia Liu; Jian Fang; Zongben Xu
Page(s): 21 - 34

3. Feature Selection Using a Neural Framework With Controlled Redundancy
Author(s): Rudrasis Chakraborty; Nikhil R. Pal
Page(s): 35 - 50

4. Pareto-Path Multitask Multiple Kernel Learning
Author(s): Cong Li; Michael Georgiopoulos; Georgios C. Anagnostopoulos
Page(s): 51 - 61

5. Learning Understandable Neural Networks With Nonnegative Weight Constraints
Author(s): Jan Chorowski; Jacek M. Zurada
Page(s): 62 - 69

6. A Latent Manifold Markovian Dynamics Gaussian Process
Author(s): Sotirios P. Chatzis; Dimitrios Kosmopoulos
Page(s): 70 - 83

7. Existence and Uniform Stability Analysis of Fractional-Order Complex-Valued Neural Networks With Time Delays
Author(s): R. Rakkiyappan; Jinde Cao; G. Velmurugan
Page(s): 84 - 97

8. Identification of the Dynamic Operating Envelope of HCCI Engines Using Class Imbalance Learning
Author(s): Vijay Manikandan Janakiraman; XuanLong Nguyen; Jeff Sterniak; Dennis Assanis
Page(s): 98 - 112

9. Synchronization of Nonlinear Coupled Networks via Aperiodically Intermittent Pinning Control
Author(s): Xiwei Liu; Tianping Chen
Page(s): 113 - 126

10. Digital Implementation of a Biological Astrocyte Model and Its Application
Author(s): Hamid Soleimani; Mohammad Bavandpour; Arash Ahmadi; Derek Abbott
Page(s): 127 - 139

11. Actor–Critic-Based Optimal Tracking for Partially Unknown Nonlinear Discrete-Time Systems
Author(s): Bahare Kiumarsi; Frank L. Lewis
Page(s): 140 - 151

12. Large-Scale Nyström Kernel Matrix Approximation Using Randomized SVD
Author(s): Mu Li; Wei Bi; James T. Kwok; Bao-Liang Lu
Page(s): 152 - 164

13. Reinforcement Learning Design-Based Adaptive Tracking Control With Less Learning Parameters for Nonlinear Discrete-Time MIMO Systems
Author(s): Yan-Jun Liu; Li Tang; Shaocheng Tong; C. L. Philip Chen; Dong-Juan Li
Page(s): 165 - 176

14. Nonsmooth ICA Contrast Minimization Using a Riemannian Nelder–Mead Method
Author(s): Suviseshamuthu Easter Selvan
Page(s): 177 - 183

Reminder: conference paper deadline FUZZ-IEEE 2015

A reminder that the deadline for submitting papers to the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) 2015 is February 8, 2015. This conference will be held in Istanbul, Turkey, August 2-5, 2015.

Reminder: conference paper deadline for IEEE CIG 2015

A reminder that the paper submission deadline for the 2015 IEEE Conference on Computational Intelligence in Games (IEEE CIG) is April 2, 2015. This conference will be held in Tainan, Taiwan, 31 August to 2 September, 2015.

Reminder: paper deadline for INNS Big Data 2015

A reminder that the deadline for submitting papers to the INNS Conference on Big Data is March 22, 2015. This conference will be held in San Francisco, USA, 8-10 August, 2015.

Database of Computational Intelligence Courses

One of the ways I contribute to the IEEE Computational Intelligence Society is by serving on the University Curricula Subcommittee of the Education Committee. Among the activities of the curricula subcommittee is maintaining a world-wide directory of courses in computational intelligence.

This directory is now available as a searchable online database, at http://ucs.ais.ac.nz/

This is a prototype of a system where educators can submit details of their courses, search existing courses, and engage in discussions with other educators about the listed courses. Anyone may access and search the database, although users must register to submit new courses or leave comments.

This system was developed as a student project by the following students:

• Pankaj Dadral
• Toshitsugu Hashimoto
• Shuxiang Wang
• Dan Mo

The project was supervised by myself and is kindly hosted by Auckland Institute of Studies, where I'm the head of the Information Technology Programme. 

Reminder: paper submission deadline: IJCNN 2015

A reminder that the paper submission deadline for the International Joint Conference on Neural Networks (IJCNN) 2015 is January 15, 2015. This conference will be held in Killarney, Ireland, July 12-17, 2015.

13th International Conference on Neuro-Computing and Evolving Intelligence 2015 (NCEI '15)

INTELLIGENT INFORMATION TECHNOLOGIES FOR BIG DATA

13th International Conference on Neuro-Computing and Evolving Intelligence 2015 (NCEI ‘15) Auckland, New Zealand, February 19-20, 2015

Venue
Auckland University of Technology
WG Sir Paul Reeves Building, level 1, room 126,
2 Governor Fitzroy Place, Auckland 1010 New Zealand

TOPICS:

• Big and Stream Data Analytics
• Spiking Neural Network Computation
• High Performance Neuromorphic System
• Novel Brain-Computer Interfaces (BCI)
• Novel Motion Data Analysis Technology
• Predictive Personalised Modelling of non-Communicable Diseases
• Predicting Response to Treatment
• Personalised Modelling in Bioinformatics
• Predictive Modelling on Ecological and Environmental Data
• Big Data in Radio-Astronomy
• Computer Vision and Image Processing for Dynamic Data Analysis
• Visualisation of Scientific Data
• Novel Human-Computer Interfaces
• Complex System Optimisation
• Collaborative and Distributed Systems Design

Selected full papers will be published after the conference in special issues of Evolving Systems and Springer Series in Bio-/Neuroinformatics.
Please visit the NCEI’15 website for more details: www.kedri.aut.ac.nz/conferences/ncei15

Special Events:

1. NZ INTERACT team discussion
2. KEDRI alumni event
3. Maori Cultural Program

IMPORTANT DATES:
Final Abstract Submission: 15 JANUARY, 2015
Acceptance Notification: 2 weeks after the submission

General Chair:
Prof. Nikola Kasabov

Organising Chair:
Joyce D’Mello
(email: jdmello@aut.ac.nz)

Web Maintenance & Tech.Support:
Elisa Capecci

Organising Committee:

• Nathan Scott (email: nascott@aut.ac.nz)
• Norhanifah Murli
• Muhaini Othman
• Paul Davidson,
• Reggio Hartono
• Fahad Alvi
• Vivienne Breen,
• Maryam Gholami
• Neelava Sengupta
• Enmei Tu
• Jin Hu

Programme Committee:

• Prof. A. Al-Jumaily
• A/Prof. D. Bailey
• Prof. M. Billinghurst
• Dr. A. Cichocki
• A/Prof. T. Clear
• Dr. A. Connor
• Prof. G. Dobbie
• Prof. V. Feigin
• A/Prof. E. Frank
• Prof. S. Furber
• Prof. S. Gulyaev
• Dr. C. Higgins
• Prof. G. Holmes
• Prof. Z. Hou
• Prof. G. Indiveri
• Prof. R. Jones
• A/Prof. F. Joseph,
• Dr. I. Khan
• Prof. R. Klette
• Dr.Y.S. Koh
• Dr. R. Krishnamurthi
• Prof. R. Kydd, Dr. D. Love
• Dr. A. Lowe
• Prof. S. MacDonell
• Dr. A. Malik
• Dr. S. Marks
• Dr. H. Nuzly
• Prof. S. Ozawa
• A/Prof. D. Parry
• A/Prof. R. Pears
• A/Prof. B. Pfahringer
• Prof. H. Regenbrecht
• Prof. A. Robins
• Dr. T. Robotham,
• Dr. B. Russell
• Dr. M. Sagar
• Prof. Z. Salcic
• Dr. S. Singamneni
• A/Prof. D. Taylor
• A/Prof. C. Walker
• Dr. G. Wang
• Dr. K. Wang
• Dr. M. Watts
• Dr. S. Weddell
• A/Prof. S. Worner
• Dr. W.Q. Yan
• Prof. J. Yang
• Prof. M. Zhang.

IEEE Transactions on Evolutionary Computation Volume 18, Number 6, December 2014

1. Parameter Optimization Algorithms for Evolving Rule Models Applied to Freshwater Ecosystems
Author(s): Cao, H. ; Recknagel, F. ; Orr, P.T.
Page(s): 793 - 806

2. An Analysis of $N!K$ Landscapes: Interaction Structure, Statistical Properties, and Expected Number of Local Optima
Author(s): Buzas, J. ; Dinitz, J.
Page(s): 807 - 818

3. The Effect of Memory Size on the Evolutionary Stability of Strategies in Iterated Prisoner's Dilemma
Author(s): Li, J. ; Kendall, G.
Page(s): 819 - 826

4. An Evolutionary Multiobjective Approach to Sparse Reconstruction
Author(s): Li, L. ; Yao, X. ; Stolkin, R. ; Gong, M. ; He, S.
Page(s): 827 - 845

5. A New Memetic Algorithm With Fitness Approximation for the Defect-Tolerant Logic Mapping in Crossbar-Based Nanoarchitectures
Author(s): Yuan, B. ; Li, B. ; Weise, T. ; Yao, X.
Page(s): 846 - 859

6. Performance Analysis of Evolutionary Algorithms for the Minimum Label Spanning Tree Problem
Author(s): Lai, X. ; Zhou, Y. ; He, J. ; Zhang, J.
Page(s): 860 - 872

7. Evolutionary Design of Decision-Tree Algorithms Tailored to Microarray Gene Expression Data Sets
Author(s): Barros, R.C. ; Basgalupp, M.P. ; Freitas, A.A. ; de Carvalho, A.C.P.L.F.
Page(s): 873 - 892

8. Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data
Author(s): Bhowan, U. ; Johnston, M. ; Zhang, M. ; Yao, X.
Page(s): 893 - 908

9. Stable Matching-Based Selection in Evolutionary Multiobjective Optimization
Author(s): Li, K. ; Zhang, Q. ; Kwong, S. ; Li, M. ; Wang, R.
Page(s): 909 - 923

IEEE Transactions on Fuzzy Systems, Volume 22, Number 6, December 2014

1. The Bounded Capacity of Fuzzy Neural Networks (FNNs) Via a New Fully Connected Neural Fuzzy Inference System (F-CONFIS) With Its Applications
Author(s): Wang, J. ; Wang, C.-H. ; Chen, C.L.P.
Page(s): 1373 - 1386

2. Joint Block Structure Sparse Representation for Multi-Input–Multi-Output (MIMO) T–S Fuzzy System Identification
Author(s): Luo, M. ; Sun, F. ; Liu, H.
Page(s): 1387 - 1400

3. Robust $L_{bm infty}$-Gain Fuzzy Disturbance Observer-Based Control Design With Adaptive Bounding for a Hypersonic Vehicle
Author(s): Wu, H.-N. ; Liu, Z.-Y. ; Guo, L.
Page(s): 1401 - 1412

4. A Novel Model-Based Controller for Polymer Extrusion
Author(s): Abeykoon, C.
Page(s): 1413 - 1430

5. Logic Connectives for Soft Sets and Fuzzy Soft Sets
Author(s): Ali, M.I. ; Shabir, M.
Page(s): 1431 - 1442

6. A Collaborative Fuzzy Clustering Algorithm in Distributed Network Environments
Author(s): Zhou, J. ; Philip Chen, C.L. ; Chen, L. ; Li, H.-X.
Page(s): 1443 - 1456

7. Multilabel Text Categorization Based on Fuzzy Relevance Clustering
Author(s): Lee, S.-J. ; Jiang, J.-Y.
Page(s): 1457 - 1471

8. Construction of Neurofuzzy Models For Imbalanced Data Classification
Author(s): Gao, M. ; Hong, X. ; Harris, C.J.
Page(s): 1472 - 1488

9. A Banzhaf Function for a Fuzzy Game
Author(s): Tan, C. ; Jiang, Z.-Z. ; Chen, X. ; Ip, W.H.
Page(s): 1489 - 1502

10. Stability Analysis of Switched Fuzzy Systems Via Model Checking
Author(s): Ding, Z. ; Zhou, Y. ; Zhou, M.
Page(s): 1503 - 1514

11. Edge-Detection Method for Image Processing Based on Generalized Type-2 Fuzzy Logic
Author(s): Melin, P. ; Gonzalez, C.I. ; Castro, J.R. ; Mendoza, O. ; Castillo, O.
Page(s): 1515 - 1525

12. Fault Tolerant Controller Design for T–S Fuzzy Systems With Time-Varying Delay and Actuator Faults: A K-Step Fault-Estimation Approach
Author(s): Huang, S.-J. ; Yang, G.-H.
Page(s): 1526 - 1540

13. A Scene Image is Nonmutually Exclusive—A Fuzzy Qualitative Scene Understanding
Author(s): Lim, C.H. ; Risnumawan, A. ; Chan, C.S.
Page(s): 1541 - 1556

14. Incremental Fuzzy Clustering With Multiple Medoids for Large Data
Author(s): Wang, Y. ; Chen, L. ; Mei, J.-P.
Page(s): 1557 - 1568

15. Multipolar Aggregation Operators in Reasoning Methods for Fuzzy Rule-Based Classification Systems
Author(s): Mesiarova-Zemankova, A.
Page(s): 1569 - 1584

16. Cluster-Centric Fuzzy Modeling
Author(s): Pedrycz, W. ; Izakian, H.
Page(s): 1585 - 1597

17. An Intelligent Second-Order Sliding-Mode Control for an Electric Power Steering System Using a Wavelet Fuzzy Neural Network
Author(s): Lin, F.-J. ; Hung, Y.-C. ; Ruan, K.-C.
Page(s): 1598 - 1611

18. Anomaly Detection and Characterization in Spatial Time Series Data: A Cluster-Centric Approach
Author(s): Izakian, H. ; Pedrycz, W.
Page(s): 1612 - 1624

19. Extension of the Fuzzy Integral for General Fuzzy Set-Valued Information
Author(s): Anderson, D.T. ; Havens, T.C. ; Wagner, C. ; Keller, J.M. ; Anderson, M.F. ; Wescott, D.J.
Page(s): 1625 - 1639

20. A Probabilistic Framework for Interval Type-2 Fuzzy Linguistic Summarization
Author(s): Boran, F.E. ; Akay, D. ; Yager, R.R.
Page(s): 1640 - 1653

21. On the Generalized Local Stability and Local Stabilization Conditions for Discrete-Time Takagi–Sugeno Fuzzy Systems
Author(s): Lee, D.H. ; Joo, Y.H.
Page(s): 1654 - 1668

22. Priorities of Intuitionistic Fuzzy Preference Relation Based on Multiplicative Consistency
Author(s): Liao, H. ; Xu, Z.
Page(s): 1669 - 1681

23. Backward Fuzzy Rule Interpolation
Author(s): Jin, S. ; Diao, R. ; Quek, C. ; Shen, Q.
Page(s): 1682 - 1698

Neural Networks Voume 61, Pages 1-118, January 2015

1. Neural Networks Referees in 2014
Pages: xi-xiii

2. Exciting Time for Neural Networks  
Pages: xv-xvi
Author(s): Kenji Doya, DeLiang Wang

NEURAL NETWORKS LETTERS

3. Dynamic analysis of periodic solution for high-order discrete-time Cohen–Grossberg neural networks with time delays  
Pages: 68-74
Author(s): Kaiyun Sun, Ancai Zhang, Jianlong Qiu, Xiangyong Chen, Chengdong Yang, Xiao Chen

REVIEWS

4. Trends in extreme learning machines: A review
Pages: 32-48
Author(s): Gao Huang, Guang-Bin Huang, Shiji Song, Keyou You

5. Deep learning in neural networks: An overview
Pages: 85-117
Author(s): Jürgen Schmidhuber

LEARNING SYSTEMS

6. An efficient sampling algorithm with adaptations for Bayesian variable selection
Pages: 22-31
Author(s): Takamitsu Araki, Kazushi Ikeda, Shotaro Akaho

7. A complex-valued neural dynamical optimization approach and its stability analysis
Pages: 59-67
Author(s): Songchuan Zhang, Youshen Xia, Weixing Zheng

8. Max–min distance nonnegative matrix factorization  
Pages: 75-84
Author(s): Jim Jing-Yan Wang, Xin Gao

MATHEMATICAL AND COMPUTATIONAL ANALYSIS

9. New synchronization criteria for memristor-based networks: Adaptive control and feedback control schemes
Pages: 1-9
Author(s): Ning Li, Jinde Cao

10. A one-layer recurrent neural network for constrained nonconvex optimization
Pages: 10-21
Author(s): Guocheng Li, Zheng Yan, Jun Wang

11. Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays
Pages: 49-58
Author(s): Guodong Zhang, Yi Shen, Quan Yin, Junwei Sun

IEEE Transactions on Neural Networks and Learning Systems, Volume 25, Number 12, December 2014

1. Adaptive Neural Control for a Class of Nonlinear Time-Varying Delay Systems With Unknown Hysteresis
Author(s): Liu, Z. ; Lai, G. ; Zhang, Y. ; Chen, X. ; Chen, C.L.P.
Page(s): 2129 - 2140

2. Optimal Control for Unknown Discrete-Time Nonlinear Markov Jump Systems Using Adaptive Dynamic Programming
Author(s): Zhong, X. ; He, H. ; Zhang, H. ; Wang, Z.
Page(s): 2141 - 2155

3. A Novel Estimation Algorithm Based on Data and Low-Order Models for Virtual Unmodeled Dynamics
Author(s): Zhang, Y. ; Chai, T. ; Sun, J. ; Chen, X. ; Wang, H.
Page(s): 2156 - 2166

4. Structure-Constrained Low-Rank Representation
Author(s): Tang, K. ; Liu, R. ; Su, Z. ; Zhang, J.
Page(s): 2167 - 2179

5. Exponential Stabilization for Sampled-Data Neural-Network-Based Control Systems
Author(s): Wu, Z. ; Shi, P. ; Su, H. ; Chu, J.
Page(s): 2180 - 2190

6. Learning Regularized LDA by Clustering
Author(s): Pang, Y. ; Wang, S. ; Yuan, Y.
Page(s): 2191 - 2201

7. A Deep Connection Between the Vapnik–Chervonenkis Entropy and the Rademacher Complexity
Author(s): Anguita, D. ; Ghio, A. ; Oneto, L. ; Ridella, S.
Page(s): 2202 - 2211

8. Learning Deep Hierarchical Visual Feature Coding
Author(s): Goh, H. ; Thome, N. ; Cord, M. ; Lim, J.
Page(s): 2212 - 2225

9. A Parsimonious Mixture of Gaussian Trees Model for Oversampling in Imbalanced and Multimodal Time-Series Classification
Author(s): Cao, H. ; Tan, V.Y.F. ; Pang, J.Z.F.
Page(s): 2226 - 2239

10. Semi-supervised Domain Adaptation on Manifolds
Author(s): Cheng, L. ; Pan, S.J.
Page(s): 2240 - 2249

11. Real-Time Gesture Interface Based on Event-Driven Processing From Stereo Silicon Retinas
Author(s): Lee, J.H. ; Delbruck, T. ; Pfeiffer, M. ; Park, P.K.J. ; Shin, C. ; Ryu, H. ; Kang, B.C.
Page(s): 2250 - 2263

12. Adaptive Neural PD Control With Semiglobal Asymptotic Stabilization Guarantee
Author(s): Pan, Y. ; Yu, H. ; Er, M.J.
Page(s): 2264 - 2274

13. Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification
Author(s): Bi, W. ; Kwok, J.T.
Page(s): 2275 - 2287

14. Synchronization in an Array of Output-Coupled Boolean Networks With Time Delay
Author(s): Zhong, J. ; Lu, J. ; Liu, Y. ; Cao, J.
Page(s): 2288 - 2294

15. Hybrid Manifold Embedding
Author(s): Liu, Y. ; Liu, Y. ; Chan, K.C.C. ; Hua, K.A.
Page(s): 2295 - 2302

16. Learning Deep and Wide: A Spectral Method for Learning Deep Networks
Author(s): Shao, L. ; Wu, D. ; Li, X.
Page(s): 2303 - 2308

17. On the Additive Properties of the Fat-Shattering Dimension
Author(s): Asor, O. ; Duan, H.H. ; Kontorovich, A.
Page(s): 2309 - 2312

Reminder: paper submission deadline for CEC 2015

A reminder that the deadline for submitting papers to the IEEE Congress on Evolutionary Computation (IEEE CEC) 2015 is December 19, 2014. This conference will be held in Sendai, Japan, 25-28 May, 2015.

Reminder: conference paper deadline FUZZ-IEEE 2015

A reminder that the deadline for submitting papers to the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) 2015 is February 8, 2015. This conference will be held in Istanbul, Turkey, August 2-5, 2015.

IEEE Transactions on Neural Networks and Learning Systems: Volume 25, Issue 11, November 2014

1. Online PLSA: Batch Updating Techniques Including Out-of-Vocabulary Words
Author(s): Nikoletta K. Bassiou; Constantine L. Kotropoulos
Page(s): 1953 - 1966

2. A Gaussian Process Model for Data Association and a Semidefinite Programming Solution
Author(s): Miguel Lazaro-Gredilla; Steven Van Vaerenbergh
Page(s): 1967 - 1979

3. Mahalanobis Distance on Extended Grassmann Manifolds for Variational Pattern Analysis
Author(s): Yoshikazu Washizawa; Seiji Hotta
Page(s): 1980 - 1990

4. Divisive Gaussian Processes for Nonstationary Regression
Author(s): Luis Munoz-Gonzalez; Miguel Lazaro-Gredilla; Anibal R. Figueiras-Vidal
Page(s): 1991 - 2003

5. Neural Network-Based Motion Control of an Underactuated Wheeled Inverted Pendulum Model
Author(s): Chenguang Yang; Zhijun Li; Rongxin Cui; Bugong Xu
Page(s): 2004 - 2016

6. Adaptive Neural Control of MIMO Nonlinear Systems With a Block-Triangular Pure-Feedback Control Structure
Author(s): Zhenfeng Chen; Shuzhi Sam Ge; Yun Zhang; Yanan Li
Page(s): 2017 - 2029

7. Single-Trial Classification of Event-Related Potentials in Rapid Serial Visual Presentation Tasks Using Supervised Spatial Filtering
Author(s): Hubert Cecotti; Miguel P. Eckstein; Barry Giesbrecht
Page(s): 2030 - 2042

8. Multiwavelet Packet Entropy and its Application in Transmission Line Fault Recognition and Classification
Author(s): Zhigang Liu; Zhiwei Han; Yang Zhang; Qiaoge Zhang
Page(s): 2043 - 2052

9. Confabulation-Inspired Association Rule Mining for Rare and Frequent Itemsets
Author(s): Azadeh Soltani; M.-R. Akbarzadeh-T.
Page(s): 2053 - 2064

10. Discriminant Locality Preserving Projections Based on L1-Norm Maximization
Author(s): Fujin Zhong; Jiashu Zhang; Defang Li
Page(s): 2065 - 2074

11. Ordinal Neural Networks Without Iterative Tuning
Author(s): Francisco Fernandez-Navarro; Annalisa Riccardi; Sante Carloni
Page(s): 2075 - 2085

12. Local Linear Regression for Function Learning: An Analysis Based on Sample Discrepancy
Author(s): Cristiano Cervellera; Danilo Maccio
Page(s): 2086 - 2098

13. Passivity and Passification of Memristor-Based Recurrent Neural Networks With Time-Varying Delays
Author(s): Zhenyuan Guo; Jun Wang; Zheng Yan
Page(s): 2099 - 2109

14. Synchronization on Complex Networks of Networks
Author(s): Renquan Lu; Wenwu Yu; Jinhu Lv; Anke Xue
Page(s): 2110 - 2118

15. Real-Time Keypoint Recognition Using Restricted Boltzmann Machine
Author(s): Miaolong Yuan; Huajin Tang; Haizhou Li
Page(s): 2119 - 2126

Conference paper deadline: ICAISC 2015

The deadline for submitting papers to the 14th International Conference on Artificial Intelligence and Soft Computing (ICAISC) 2015 is November 20, 2014. This conference will be held in Zakopane, Poland, 14-18 June 2015.