18th International Conference on Neural Information Processing

November 13-17, 2011, Majesty Plaza, Shanghai, China

Program & Abstracts

Technical Sponsors

Asia Pacific Neural Network Assembly

Japanese Neural Network Society

Financial Sponsors

National Natural Science Foundation of China

Shanghai Hyron Software Co., LTD

Hitachi (China) Research & Development

Corporation

Fujitsu Research and Development Center,

CO., LTD

 

 

Table of Content 

Welcome Message ......................................................................................................... I

ICONIP 2011 Organization ......................................................................................... III

Venue Information ....................................................................................................... IX

ICONIP2011 Technical Program at a Glance ................................................................ 1

Keynotes & Plenary Speakers ........................................................................................ 4

ICONIP2011 Technical Program ................................................................................. 14

Book of Abstracts ........................................................................................................ 33

Author Index ................................................................................................................ 88

Workshops Programs…………………...………………………………………………………99

 

 

I  

Welcome Message

On behalf of the Organizing Committee, it is our pleasure to welcome you to participate in the Eighteenth International Conference on Neural Information Processing (ICONIP2011). ICONIP is the annual conference of the Asia Pacific Neural Network Assembly (APNNA). ICONIP 2011 aims to provide a high-level international forum for scientists, engineers, educators, and students to address new challenges, share solutions, and discuss future research directions in neural information processing and real-world applications.

The scientific program of the ICONIP2011 presents an outstanding spectrum of over 260 research papers from forty two countries and regions, emerging from multidisciplinary areas such as computational neuroscience,cognitive science, computer science, neural engineering, computer vision, machine learning, pattern recognition, natural language processing, and many more to focus on the challenges of developing future technologies for neural information processing. In addition to the contributed papers, we are particularly pleased by ten plenary speeches by world-renowned scholars: Shun-ichi Amari, Kunihiko Fukushima, Aike Guo, Lei Xu, Jun Wang, DeLiang Wang, Derong Liu, Xin Yao, Soo-Young Lee, and Nikola Kasabov. The program will also include six excellent tutorials by David Cai, Irwin King, Pei-Ji Liang, Hiroshi Mamitsuka, Ming Zhou, Hang Li, and Shanfeng Zhu. The conference will be followed by three post-conference Workshops held in Hangzhou, November 18, 2011: “ICONIP2011Workshop on Brain-Computer Interface and Applications”, organized by Bao-Liang Lu, Liqing Zhang, and Chin-Teng Lin; “The 4th International Workshop on Data Mining and Cybersecurity”, organized by Paul S. Pang, Tao Ban, Youki Kadobayashi, and Jungsuk Song; and “ICONIP 2011 Workshop on Recent Advances in Nature Inspired Computation and Its Applications”, organized by Xin Yao and Shan He.

ICONIP2011 organizers would like to thank all special session organizers for their effort and time for enriching the topics and program of the conference. The program will include the following thirteen special sessions: “Advances in Computational Intelligence Methods based Pattern Recognition”, organized by Kai-Zhu Huang and Jun Sun; “Biologically Inspired Vision and Recognition”, organized by Jun Miao, Libo Ma, Liming Zhang, JuyangWeng and Xilin Chen; “Bio-Medical Data Analysis”, organized by Jie Yang and Guo-Zheng Li; “Brain Signal Processing”, organized by Jian-Ting Cao, Tomasz M. Rutkowski, Toshihisa Tanaka, and Liqing Zhang; “Brain-Realistic Models for Learning, Memory and Embodied Cognition”, organized by Huajin Tang and Jun Tani; “Clifford Algebraic Neural Networks”, organized by Tohru Nitta and Yasuaki Kuroe; “Combining Multiple Learners”, organized by Younès Bennani, Nistor Grozavu, Mohamed Nadif, and Nicoleta Rogovschi; “Computational Advances in Bioinformatics”, organized by Jonathan H. Chan; “Computational-Intelligent Human Computer Interaction”, organized by Chin-Teng Lin, Jyh-Yeong Chang, John Kar-kin Zao, Yong-Sheng Chen, and Li-Wei Ko;

II  

“Evolutionary Design and Optimisation”, organized by RuhulSarker and Mao-Lin Tang; “Human-Originated Data Analysis and Implementation”, organized by Hyeyoung Park and Sang-Woo Ban; “Natural Language Processing and Intelligent Web Information Processing”, organized by Xiao-Long Wang, Rui-Feng Xu, and Hai Zhao; and “Integrating Multiple Nature-inspired Approaches”, organized by Shan He and Xin Yao. The ICONIP2011 and the post-conference Workshops events would not have achieved their success without the generous contributions of many organizations and volunteers. The organizers would also like to express sincere thanks to APNNA for the sponsorship, to the Chinese Neural Networks Council, International Neural Network Society, and Japanese Neural Network Society for their technical co-sponsorship, to Shanghai Jiao Tong University for its financial and logistic supports, and to National Natural Science Foundation of China, Shanghai Hyron Software Co., LTD, Microsoft Research Asia, Hitachi (China) Research & Development Corporation, Fujitsu Research and Development Center, CO., LTD, and Eagle Canyon for their financial supports. We are very pleased to acknowledge the support of the conference Advisory Committee, the APNNA Governing Board and Past Presidents for their guidance, and the members of the International Program Committee and additional reviewers for reviewing the papers. Particularly, the organizers would like to thank the proceedings publisher, Springer, for publishing the proceedings in Lecture Notes in Computer Science. We want to give special thanks to Web managers, HaoyuCai and Dong Li, and the publication team comprising Li-Chen Shi, Yong Peng, Cong Hui, Bing Li, Dan Nie, Ren-Jie Liu, Tian-Xiang Wu, Xue-Zhe Ma, Shao-Hua Yang, Yuan-Jian Zhou and Cong Xie for checking the accepted papers in a short period of time. Last but not least, the organizers would like to thank all the authors, speakers, audience, and volunteers. We hope that you enjoy your time in Shanghai as well as the technical and social programs at ICONIP2011. Yours Sincerely,

Liqing Zhang

Bao-Liang Lu James T. Kwok

ICONIP2011 General Chair ICONIP2011 Program Co-Chairs

III  

 

ICONIP 2011 Organization

Organizer

Shanghai Jiao Tong University

Sponsor

Asia Pacific Neural Network Assembly

Financial Co-sponsors

Shanghai Jiao Tong University

National Natural Science Foundation of China

Shanghai Hyron Software Co., LTD

Microsoft Research Asia

Hitachi (China) Research & Development Corporation

Fujitsu Research and Development Center, Co., LTD

Eagle Canyon

Technical Co-sponsors

China Neural Networks Council

International Neural Network Society

Japanese Neural Network Society

Honorary Chair

Shun-ichi Amari, Brain Science Institute, RIKEN, Japan

Advisory Committee Chairs

Shoujue Wang, Institute of Semiconductors, Chinese Academy of Sciences, China

Aike Guo, Institute of Neuroscience, Chinese Academy of Sciences, China

Liming Zhang, Fudan University, China

Advisory Committee Members

Sabri Arik, Istanbul University, Turkey

Jonathan H. Chan, King Mongkut'sUniversity of Technology, Thailand

Wlodzislaw Duch, Nicolaus Copernicus University, Poland

Tom Gedeon, Australian National University, Australia

Yuzo Hirai, University of Tsukuba, Japan

Ting-Wen Huang, Texas A&M University, Qatar

Akira Hirose, University of Tokyo, Japan

Nik Kasabov, AucklandUniversity of Technology, New Zealand

Irwin King, The Chinese University of Hong Kong, Hong Kong

Weng-Kin Lai, MIMOS, Malaysia

Min-Ho Lee, Kyungpoor National University, Korea

Soo-Young Lee, Korea Advanced Institute of Science and Technology, Korea

IV  

Andrew Chi-Sing Leung, CityUniversity of Hong Kong, Hong Kong

Chin-Teng Lin, National Chiao Tung University, Taiwan

Derong Liu, University of Illinois at Chicago, USA

Noboru Ohnishi, Nagoya University, Japan

Nikhil R. Pal, Indian Statistical Institute, India

John Sum, National Chung Hsing University, Taiwan

DeLiang Wang, Ohio State University, USA

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

Kevin Wong, Murdoch University, Australia

Lipo Wang, Nanyang Technological University, Singapore

Xin Yao, University of Birmingham, UK

Liqing Zhang, Shanghai Jiao Tong University, China

General Chair

Bao-Liang Lu, Shanghai Jiao Tong University, China

Program Chairs

Liqing Zhang, Shanghai Jiao Tong University, China

James T.Y. Kwok, Hong KongUniversity of Science and Technology, Hong Kong

Organizing Chair

Hongtao Lu, Shanghai Jiao Tong University, China

Workshop Chairs

Guangbin Huang, Nanyang Technological University, Singapore

Jie Yang, Shanghai Jiao Tong University, China

Xiaorong Gao, Tsinghua University, China

Special Sessions Chairs

Changshui Zhang, Tsinghua University, China

Akira Hirose, University of Tokyo, Japan

Minho Lee, Kyungpoor National University, Korea

Tutorial Chair

Si Wu, Institute of Neuroscience, Chinese Academy of Sciences, China

Publications Chairs

Yuan Luo, Shanghai Jiao Tong University, China

Tianfang Yao, Shanghai Jiao Tong University, China

Yun Li, NanjingUniversity of Posts and Telecommunications, China

Publicity Chairs

Kazushi Ikeda, Nara Institute of Science and Technology, Japan

Shaoning Pang, Unitec Institute of Technology, New Zealand

V  

Chi-Sing Leung, City University of Hong Kong, China

Registration Chair

Hai Zhao, Shanghai Jiao Tong University, China

Financial Chair

YangYang, Shanghai Maritime University, China

Local Arrangement Chairs

Guang Li, Zhejiang University, China

Fang Li, Shanghai Jiao Tong University, China

Secretary

Xun Liu, Shanghai Jiao Tong University, China

Program Committee

Shigeo Abe

Bruno Apolloni

Sabri Arik

Sang-Woo Ban

Jianting Cao

Jonathan Chan

Songcan Chen

Xilin Chen

Yen-Wei Chen

Yiqiang Chen

Siu-Yeung David Cho

Sung-Bae Cho

Seungjin Choi

Andrzej Cichocki

Jose Alfredo Ferreira Costa

Sergio Cruces

Ke-Lin Du

Simone Fiori

John Qiang Gan

Junbin Gao

Xiaorong Gao

Nistor Grozavu

Ping Guo

Qing-Long Han

Shan He

Akira Hirose

Jinglu Hu

Guang-Bin Huang

Kaizhu Huang

Amir Hussain

Danchi Jiang

Tianzi Jiang

Tani Jun

Joarder Kamruzzaman

Shunshoku Kanae

Okyay Kaynak

John Keane

Sungshin Kim

Li-Wei Ko

Takio Kurita

Minho Lee

Chi Sing Leung

Chunshien Li

Guo-Zheng Li

Junhua Li

Wujun Li

Yuanqing Li

Yun Li

Huicheng Lian

Peiji Liang

Chin-Teng Lin

Hsuan-Tien Lin

Hongtao Lu

Libo Ma

Malik Magdon-Ismail

Robert(Bob) McKay

VI  

Duoqian Miao

Jun Miao

Vinh Nguyen

Tohru Nitta

Toshiaki Omori

Hassab Elgawi Osman

Seiichi Ozawa

Paul Pang

Hyeyoung Park

Alain Rakotomamonjy

Sarker Ruhul

Naoyuki Sato

Lichen Shi

Jochen J. Steil

John Sum

Jun Sun

Toshihisa Tanaka

Huajin Tang

Maolin Tang

Dacheng Tao

Qing Tao

Peter Tino

Ivor Tsang

Michel Verleysen

Bin Wang

Rubin Wang

Xiao-Long Wang

Yimin Wen

Young-Gul Won

Yao Xin

Rui-Feng Xu

Haixuan Yang

Jie Yang

Yang Yang

Yingjie Yang

Zhirong Yang

Dit-Yan Yeung

Jian Yu

Zhigang Zeng

Jie Zhang

Kun Zhang

Hai Zhao

Zhihua Zhou

Reviewers Pablo Aguilera

Lifeng Ai

Elliot Anshelevich

Bruno Apolloni

Sansanee Auephanwiriyakul

Hongliang Bai

Rakesh Kr Bajaj

Tao Ban

Gang Bao

Simone Bassis

Anna Belardinelli

Yoshua Bengio

Sergei Bezobrazov

Yinzhou Bi

Alberto Borghese

Tony Brabazon

Guenael Cabanes

Faicel Chamroukhi

Feng-Tse Chan

Hong Chang

Liang Chang

Aaron Chen

Caikou Chen

Huangqiong Chen

Huanhuan Chen

Kejia Chen

Lei Chen

Qingcai Chen

Yin-Ju Chen

Yuepeng Chen

Jian Cheng

Wei-Chen Cheng

Yu Cheng

Seong-Pyo Cheon

Minkook Cho

Heeyoul Choi

Yong-Sun Choi

Shihchieh Chou

Angelo Ciaramella

Sanmay Das

Satchidananda Dehuri

Ivan Duran Diaz

Tom Diethe

Ke Ding

Lijuan Duan

Chunjiang Duanmu

Sergio Escalera

Aiming Feng

Remi Flamary

Gustavo Fontoura

Zhenyong Fu

Zhouyu Fu

Xiaohua Ge

Alexander Gepperth

M.Mohamad Ghassany

Adilson Gonzaga

Alexandre Gravier

Jianfeng Gu

Lei Gu

Zhong-Lei Gu

VII  

Naiyang Guan

Pedro Antonio Gutiérrez

Jing-Yu Han

Xianhua Han

Ross Hayward

Hanlin He

Akinori Hidaka

Hiroshi Higashi

Arie Hiroaki

Eckhard Hitzer

Gray Ho

Kevin Ho

Xia Hua

Mao Lin Huang

Qinghua Huang

Sheng-Jun Huang

Tan Ah Hwee

Kim Min Hyeok

Teijiro Isokawa

Wei Ji

Zheng Ji

Caiyan Jia

Nanlin Jin

Liping Jing

Yoonseop Kang

Chul Su Kim

Kyung-Joong Kim

Saehoon Kim

Yong-Deok Kim

Irwin King

Jun Kitazono

Masaki Kobayashi

Yasuaki Kuroe

Hiroaki Kurokawa

Chee Keong Kwoh

James Kwok

Lazhar Labiod

Darong Lai

Yuan Lan

Kittichai Lavangnananda

John Lee

Maylor Leung

Peter Lewis

Fuxin Li

Gang Li

Hualiang Li

Jie Li

Ming Li

Sujian Li

Xiaosong Li

Yu-feng Li

Yujian Li

Sheng-Fu Liang

Shu-Hsien Liao

CheePeng Lim

Bingquan Liu

Caihui Liu

Jun Liu

Xuying Liu

Zhiyong Liu

Hung-Yi Lo

Huma Lodhi

Gabriele Lombardi

Qiang Lu

Cuiju Luan

Abdelouahid Lyhyaoui

Bingpeng Ma

Zhiguo Ma

Laurens Van Der Maaten

Singo Mabu

Shue-Kwan Mak

Asawin Meechai

Limin Meng

Komatsu Misako

Alberto Moraglio

Morten Morup

Mohamed Nadif

Kenji Nagata

Quang Long Ngo

Phuong Nguyen

Dan Nie

Kenji Nishida

Chakarida Nukoolkit

Robert Oates

Takehiko Ogawa

Zeynep Orman

Jonathan Ortigosa-Hernandez

Mourad Oussalah

Takashi J. Ozaki

Neyir Ozcan

Pan Pan

Paul S. Pang

Shaoning Pang

Seong-Bae Park

Sunho Park

Sakrapee Paul

Helton Maia Peixoto

Yong Peng

Jonas Peters

Somnuk Phon-Amnuaisuk

J.A.Fernandez Del Pozo

Santitham Prom-on

Lishan Qiao

Yuanhua Qiao

Laiyun Qing

Yihong Qiu

Shah Atiqur Rahman

Alain Rakotomamonjy

Leon Reznik

Nicoleta Rogovschi

Alfonso E. Romero

Fabrice Rossi

Gain Paolo Rossi

Alessandro Rozza

Tomasz Rutkowski

Nishimoto Ryunosuke

Murat Saglam

Treenut Saithong

Chunwei Seah

Lei Shi

Katsunari Shibata

A. Soltoggio

Bo Song

Guozhi Song

Lei Song

Ong Yew Soon

Liang Sun

Yoshinori Takei

Xiaoyang Tan

Chaoying Tang

Lei Tang

Le-Tian Tao

VIII  

Jon Timmis

Yohei Tomita

Ming-Feng Tsai

George Tsatsaronis

Grigorios Tsoumakas

Thomas Villmann

Deng Wang

Frank Wang

Jia Wang

Jing Wang

Jinlong Wang

Lei Wang

Lu Wang

Ronglong Wang

Shitong Wang

Shuo Wang

Weihua Wang

Weiqiang Wang

Xiaohua Wang

Xiaolin Wang

Yuanlong Wang

Yunyun Wang

Zhikun Wang

Yoshikazu Washizawa

Bi Wei

Kong Wei

Yodchanan Wongsawat

Ailong Wu

Jiagao Wu

Jianxin Wu

Qiang Wu

Si Wu

Wei Wu

Wen Wu

Bin Xia

Chen Xie

Zhihua Xiong

Bingxin Xu

Weizhi Xu

Yang Xu

Xiaobing Xue

Dong Yang

Wei Yang

Wenjie Yang

Zi-Jiang Yang

Tianfang Yao

Nguwi Yok Yen

Florian Yger

Chen Yiming

Jie Yin

Lijun Yin

Xucheng Yin

Xuesong Yin

JihoYoo

Washizawa Yoshikazu

Motohide Yoshimura

Hongbin Yu

Qiao Yu

Weiwei Yu

Ying Yu

Jeong-Min Yun

Zeratul Mohd Yusoh

Yiteng Zhai

Biaobiao Zhang

Danke Zhang

Dawei Zhang

Junping Zhang

Kai Zhang

Lei Zhang

Liming Zhang

Liqing Zhang

Lumin Zhang

Puming Zhang

Qing Zhang

Rui Zhang

Tao Zhang

Tengfei Zhang

Wenhao Zhang

Xianming Zhang

Yu Zhang

Zehua Zhang

Zhifei Zhang

Jiayuan Zhao

Liang Zhao

Qi Zhao

Qibin Zhao

Xu Zhao

Haitao Zheng

Guoqiang Zhong

Wenliang Zhong

Dong-Zhuo Zhou

Guoxu Zhou

Hongming Zhou

Rong Zhou

Tianyi Zhou

Xiuling Zhou

Wenjun Zhu

Zhanxing Zhu

Fernando José Von Zube

 

IX  

Venue Information

2011 International Conference on Neural Information Processing (ICONIP 2011) will be held at

Majesty Plaza in Shanghai, China from November 13th to 17th, 2011. The hotel is located at 700

Jiujiang Road, Shanghai.

 

 

 

 

 

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X  

 

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4  

Keynotes & Plenary Speakers

Keynote Speech

Stable and Fast Decision by Neural Networks: Fundamental Problems in Mathematical Neuroscience

Shun-ichi Amari

RIKEN Brain Science Institute, Japan

Abstract

The brain, a network consisting of a vast number of neurons, processes information by dynamic interactions of neurons. A neuron receives signals from other neurons and its decision is based on the weighted sum of other signals. Such a decision is called a generalized majority decision. There are many other biological and social systems subject to the generalized majority decision. We search for the fundamental properties of a network of majority decision compared with Boolean logical decision. To this end, we consider a network of randomly connected binary neurons, having 2n states, n the number of neurons. We search for the average number of attractors and the average length of transient periods. We show by using the statistical neurodynamic method that these are extremely small compared to those of a random Boolean network. This is a characteristic feature of a neural network which guarantees quick and reliable decision, because of short transient periods.

We further study dynamics of excitation patterns in a two-dimensional neural field, showing existence of traveling bumps and the way of their control. The collision of traveling bumps shows a possibility of a new style of information processing in a neural field.

Biography

Shun-ichiAmari was born in Tokyo, Japan, on January 3, 1936. He graduated from the Graduate School of the University of Tokyo in 1963 majoring in mathematical engineering and received Dr. Eng. Degree.

He worked as an Associate Professor at Kyushu University and the University of Tokyo, and then a Full professor at the University of Tokyo, and is now Professor-Emeritus. He served as Director of RIKEN Brain Science Institute for five years, and is now its senior advisor. He has been engaged in research in wide areas of mathematical engineering, in particular, mathematical foundations of neural networks, including statistical neurodynamics, dynamical theory of neural fields, associative memory, self-organization, and general learning theory. Another main subject of his research is information geometry initiated by himself, which provides a new powerful method to information sciences and neural networks.

Dr. Amari served as President of Institute of Electronics, Information and Communication Engineers, Japan and President of International Neural Networks Society. He received Emanuel A. Piore Award and Neural Networks Pioneer Award from IEEE, the Japan Academy Award, Gabor Award from INNS, Caianiello Award, and C&C award, among many others.

5  

Plenary Talk

Recent Advances in the Neocognitron: Robust Recognition of Visual Patterns

Kunihiko Fukushima

Fuzzy Logic Systems Institute, Japan.

Abstract

The neocognitron is a neural network model proposed by Fukushima (1980). Its architecture was suggested by neurophysiological findings on the visual systems of mammals. It is a hierarchical multi-layered network. It acquires the ability to robustly recognize visual patterns through learning. Although the neocognitron has a long history, modifications of the network to improve its performance are still going on.

In this talk, after a brief introduction of the neocognitron, we discuss several improvements applied recently to the neocognitron.

They are: a) competitive learning with winner-kill-loser rule; b) subtractive inhibition for feature-extracting S-cells, which increases robustness against background noise; c) several methods for extracting oriented edges; d) blurring operation with root-mean-square by C-cells; and so on.

We also show that several new functions can be realized by introducing top-down connections to the neocognitron: a) recognition and completion of partly occluded patterns; b) restoring occluded contours, and so on.

Biography

Kunihiko Fukushima received a B.Eng. degree in electronics in 1958 and a PhD degree in electrical engineering in 1966 from Kyoto University, Japan. He was a professor at Osaka University from 1989 to 1999, at the University of Electro-Communications from 1999 to 2001, at Tokyo University of Technology from 2001 to 2006, and a visiting professor at Kansai University from 2006 to 2010. Prior to his Professorship, he was a Senior Research Scientist at the NHK Science and Technical Research Laboratories. He is now a Senior Research Scientist at Fuzzy Logic Systems Institute.

He is one of the pioneers in the field of neural networks and has been engaged in modeling neural networks of the brain since 1965.

His special interests lie in modeling neural networks of the higher brain functions, especially the mechanism of the visual system.

He was the founding President of JNNS (Japanese Neural Network Society) and a founding member on the Board of Governors of INNS (International Neural Network Society). He is a former President of APNNA (Asia-Pacific Neural Network Assembly).

6  

Plenary Talk

Automatic Model SelectionDuringLearning: A Comparative Overview Lei Xu

Chinese University of Hong Kong, Hong Kong

Abstract

A conventional implementation of model selection consists of two stages. One stage enumerates a set of candidate models with the unknown parameters of each candidate estimated by the maximum likelihood learning. The other stage selects the best candidate by one of typical criteria, e.g., AIC, BIC/MDL,HQC. This implementation suffers huge computation and provides unreliable parameter estimation on oversized candidates. One road to tackle this challenge is automatic model selection, i.e., the implementation of a learning principle yields an intrinsic mechanism that drives certain indicators of redundant substructures towards zero, by which these substructures are discarded. This talk makes a comparative overview on several streams of efforts related to this topic in two decades. One consists of heuristic learning rules featured by a mechanism of rival penalized competitive learning and further extensions. Others are Bayesian approaches with help of appropriate priors, including sparse learning, minimum message length, and variational Bayes. Another Bayesian related framework is Bayesian Ying-Yang harmony learning, which is capable of automatic model selection even without imposing priors, and can be further improved with priors incorporated. Empirical comparisons are illustrated on simulated and real datasets for tasks of clustering analyses, image segmentation, speech recognition, and radar target recognition.

Biography

Lei Xu, chair professor of Chinese Univ. Hong Kong (CUHK), Fellow of IEEE (2001-), Fellow of International Association for Pattern Recognition (2002-), and Academician of European Academy of Sciences (2002-). He completed his Ph.D thesis at Tsinghua Univ. by the end of 1986, became postdoc at Peking Univ. in 1987, then promoted to associate professor in 1988 and a professor in 1992. During 1989-93 he was research associate and postdoc in Finland, Canada and USA, including Harvard and MIT. He joined CUHK as senior lecturer in 1993, professor in 1996, and chair professor in 2002. He published several well-cited papers on neural networks, statistical learning, and pattern recognition, e.g., his papers got over 3400 citations (SCI) and over 6300 citations by Google Scholar (GS), with the top-10 papers scored over 2100(SCI) and 4100(GS). One paper scored 790(SCI) and 1351 (GS). He served as a past governor of international neural network society (INNS), a past president of APNNA, and a member of Fellow committee of IEEE CI Society. He received several national and international academic awards (e.g., 1993 National Nature Science Award, 1995 INNS Leadership Award and 2006 APNNA Outstanding Achievement Award).

7  

Plenary Talk

Implicit Intention Recognition and Hierarchical Knowledge Development for Artificial Cognitive Systems

Soo-Young Lee

Korea Advanced Institute of Science and Technology, Korea

Abstract

Artificial Cognitive Systems (ACS) is under development based on mathematical models of higher cognitive functions for human-like functions such as vision, auditory, inference, and behaviour. Although the final goal is to provide human-like decision making and behaviour, we are currently focusing on hierarchical knowledge development and recognition of both explicit and implicit human intention. In real world applications these are the core components for robust situation awareness capability, which is directly related to the decision making and behaviour. We propose to utilize multimodal cognitive neuroscience data such as fMRI, EEG, eye gaze, and GSR.

Recognition of human intention is very critical for the awareness of situation involving people. Although current human-machine interfaces have been developed to utilize explicitly-represented human intention such as keystrokes, gesture, and speech, the actual hidden human intention may be different from the explicit one. Also, people may not want to go through tedious processes to present their intentions explicitly, especially for routine sequential tasks and/or sensitive personal situations. Therefore, it is desirable to understand the hidden or unrepresented intention, i.e., 'implicit' intention, for the next-generation intelligent human-oriented user interface. We had measured multimodal signals, i.e., EEG, ECG, GSR, video, and eye gaze signals, while the subjects are asked both obvious and non-obvious questions. The latter includes sensitive personal questions which may incur differences between the explicit and implicit intentions. Also, the subjects made 'Yes' or "No' answer for each question by speech. The measured signals for the obvious questions are regarded as the references, which are used to understand the non-obvious cases. We had separately trained SVM classifiers for each modality from the obvious questions, and tested the SVMs for the non-obvious questions. The agreement (or disagreement) among different modality, and the explicitly-represented intention are analyzed. It demonstrated the possibility of understanding human implicit intention, i.e., classifying into categories, from brain and/or speech signals, which may be utilized as a next-generation human-machine interface.

Biography Soo-Young Lee received B.S., M.S., and Ph.D. degrees from Seoul National University in 1975, Korea Advanced Institute of Science in 1977, and Polytechnic Institute of New York in 1984, respectively. From 1982 to 1985 he also worked for General Physics Corporation at Columbia, MD, USA. In early 1986 he joined the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology. In 1997 he established Brain Science Research Center, which is the main research organization for the Korean Brain Neuroinformatics Research Program from 1998 to 2008. His research interests have resided in Artificial Brain, alias Artificial Cognitive Systems, i.e., the human-like intelligent systems based on biological information processing mechanism in our brain. Especially, he is interested in combining computational neuroscience and information theory for feature extraction, blind signal separation, and top-down attention. He is a Past-President of Asia-Pacific Neural Network Assembly. He received Leadership Award and Presidential Award from International Neural Network Society in 1994 and 2001, respectively, and APPNA Service Award and APNNA Outstanding Achievement Award from Asia-Pacific Neural Network Assembly in 2004 and 2009, respectively. From SPIE he also received Biomedical Wellness Award and ICA Unsupervised Learning Pioneer Award in 2008 and 2010, respectively.

8  

Plenary Talk

Dopamine Reveals Neural Circuit Mechanisms of Value Based Decision Making in Fruit Fly’s Brain

Aike Guo

Institute of Neuroscience, SIBS, CAS and Institute of Biophysics, CAS,China.

Abstract

Why fruit Fly’s brain? Drosophila Brain is the geometrical mean between the simplest and the more complicated nervous system. Drosophila transformed developmental genetics and cell biology. Now it is poised to help biologists decipher how the brain works (Claude Desplan, 2007).

Why decision making? "Life is endless series of Decision, regardless of Drosophila or Human beings" to survive, is to make decision. There are two conceptual frameworks of decision-making: simple perception decision and simple value based decision. The neuroeconomics is to explore the brain mechanisms responsible for these evaluative processes, and to explore an animal’s internal valuation of competing alternatives (Sugrue et al., 2005).Here we show that even Drosophila can make clear-cut, salience-based decisions when faced with competing alternatives.

Why mushroom body? Where does the decision making occur in fly’s brain? Mushroom bodies might be the centers of endowing an insect with a degree of “free will”or “intelligent control”over instinctive actions (F.Dujardin, 1850). We found genetic silencing of Mbs impairs decision.

Why Dopamine? The neurotransmitter dopamine (DA) plays a crucial role in motivational control: rewarding, aversive, and alerting (Bromberg-Martin et al, 2010). Using binary expression system: GAL4-Enhancer Trapping & Region-Specific Gene Expression.We revealed that the decision making in Drosophila consists of two phases: an early phase that requiring DA and MB activities and a late phase independent of these activities. Thus, we suggested that the DA-MB circuit regulates salience-based decision making in Drosophila by both gating inhibition and gain-control mechanisms (Zhang et al., 2007; Guo et al., 2009; Guo et al., 2010; Wu and Guo, 2011).

Biography

Dr. Aike Guo，biophysicist and neuroscientist，graduated from Moscow State University, Dept. of Biophysics, in 1965. He received Dr.rer.nat.from Munich University, Germany, in 1979. He has been a visiting scholar funded by Max-Planck-Society in MPI for Biological Cybernetics from 1982 to 1984. He became an academician of the Chinese Academy of Sciences (CAS) in 2003. He is currently a senior investigator and head of the Laboratory of Learning and Memory at Institute of Neuroscience (ION), Shanghai Institutes for Biological Sciences (SIBS), from 1999. He is also a research professor of Institute of Biophysics (IBP), CAS.

During 1979-1992, Dr. Guo has been working in the field of Biophysics, Visual Information Processing and Computational Neuroscience. In the past of 17 years, he has been engaged in the study about the learning and memory using fruit flies (Drosophila) as a model organism from Gene-Brain-Behavior perspective.

His current research interests are focusing in leaning/ memory and visual cognition in Drosophila. His long term goal is to explore the “first principlesof high level cognitive activities in Drosophila brain from an evolutional perspective, to shed new light on the “Brain-Mind Problem.

9  

Plenary Talk

A Classification Approach to the Cocktail Party Problem

DeLiang Wang

The Ohio State University, USA

Abstract

The cocktail party problem, also known as the speech segregation problem, has evaded a solution for decades in speech and audio processing. Motivated by recent advances in psychoacoustics and computational auditory scene analysis, I will advocate a new formulation to this old problem: instead of aiming at extracting the target speech, it classifies time-frequency units into two classes: those dominated by the target speech and the rest. This new formulation shifts the emphasis from signal estimation to signal classification, with an important implication that the cocktail party problem is now open to a plethora of binary classification techniques in neural networks and machine learning. I will discuss recent speech segregation algorithms that adopt the binary classification formulation, and the segregation performance of these systems represents considerable progress towards solving the cocktail party problem.

Biography

DeLiang Wang received the B.S. degree in 1983 and the M.S. degree in 1986 from Peking (Beijing) University, Beijing, China, and the Ph.D. degree in 1991 from the University of Southern California, Los Angeles, CA, all in computer science.

From July 1986 to December 1987 he was with the Institute of Computing Technology, Academia Sinica, Beijing. Since 1991, he has been with the Department of Computer Science & Engineering and the Center for Cognitive Science at The Ohio State University, Columbus, OH, where he is a Professor. From October 1998 to September 1999, he was a visiting scholar in the Department of Psychology at Harvard University, Cambridge, MA. From October 2006 to June 2007, he was a visiting scholar at Oticon A/S, Denmark.

Dr. Wang's research interests include machine perception and neurodynamics. Among his recognitions are the Office of Naval Research Young Investigator Award in 1996, the 2005 Outstanding Paper Award from IEEE Transactions on Neural Networks, and the 2008 Helmholtz Award from the International Neural Network Society. He is an IEEE Fellow, and currently serves as Co-Editor-in-Chief of Neural Networks.

10  

Plenary Talk

Self-Learning Control of Nonlinear Systems based on Iterative Adaptive Dynamic Programming Approach

Derong Liu

University of Illinois at Chicago, USA

Abstract

Unlike the optimal control of linear systems, the optimal control of nonlinear systems often requires solving the nonlinear Hamilton-Jacobi-Bellman (HJB) equation instead of the Riccati equation. The discrete-time HJB (DTHJB) equation is more difficult to work with than the Riccati equation because it involves solving nonlinear partial difference equations. Though dynamic programming has been an useful computational technique in solving optimal control problems for many years, it is often computationally untenable to run it to obtain the optimal solution, due to the backward numerical process required for its solutions, i.e., the well-known "curse of dimensionality". A self-learning control scheme for unknown nonlinear discrete-time systems with discount factor in the cost function is developed for this purpose. An iterative adaptive dynamic programming algorithm via globalized dual heuristic programming technique is developed to obtain the optimal controller with convergence analysis. Neural networks are used as parametric structures to facilitate the implementation of the iterative algorithm, which will approximate at each iteration the cost function, the optimal control law, and the unknown nonlinear system, respectively. Simulation examples are provided to verify the effectiveness of the present self-learning control approach.

Biography

Derong Liu received the Ph.D. degree in electrical engineering from the University of Notre Dame in 1994. He was a Staff Fellow with General Motors R&D Center, Warren, MI, from 1993 to 1995. He was an Assistant Professor in the Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, from 1995 to 1999. He joined the University of Illinois at Chicago in 1999, where he became a Full Professor of Electrical and Computer Engineering and of Computer Science in 2006. He was selected for the 100 Talents Program by the Chinese Academy of Sciences in 2008. He has published nine books. Dr. Liu is the Editor-in-Chief of the IEEE Transactions on Neural Networks and an Associate Editor of the IEEE Transactions on Control Systems Technology, Neurocomputing and the International Journal of Neural Systems. He was an elected AdCom member of the IEEE Computational Intelligence Society (2006-2008). He received the Harvey N. Davis Distinguished Teaching Award from Stevens Institute of Technology (1997), the Faculty Early Career Development (CAREER) Award from the National Science Foundation (1999), the University Scholar Award from University of Illinois (2006), and the Overseas Outstanding Young Scholar Award from the National Natural Science Foundation of China (2008).

11  

Plenary Talk

The State of the Art of Neurodynamic Optimization Jun Wang

Chinese University of Hong Kong, Hong Kong

Abstract

As an important tool for science research and engineering applications, optimization is omnipresent in a wide variety of settings. It is computationally challenging when optimization procedures have to be performed in real time to optimize the performance of dynamical systems. For such applications, classical optimization techniques may not be competent due to the problem dimensionality and stringent requirement on computational time. New paradigms are needed. One very promising approach to dynamic optimization is to apply artificial neural networks. Because of the inherent nature of parallel and distributed information processing in neural networks, the convergence rate of the solution process is not decreasing as the size of the problem increases. This talk will present the state of the art of neurodynamic optimization models and selected applications. Specifically, starting from the motivation of neurodynamic optimization, we will review various recurrent neural network models for optimization. Theoretical results about the stability and optimality of the neurodynamic optimization models will be given along with illustrative examples and simulation results. It will be shown that many computational problems can be readily solved by using the neurodynamic optimization models.

Biography

Jun Wang is a Professor in the Department of Mechanical and Automation Engineering at the Chinese University of Hong Kong. Prior to this position, he held various academic positions at Dalian University of Technology, Case Western Reserve University, and University of North Dakota. He also held various short-term visiting positions at USAF Armstrong Laboratory (1995), RIKEN Brain Science Institute (2001), Universite Catholique de Louvain (2001), Chinese Academy of Sciences (2002), Huazhong University of Science and Technology (2006~007), and Shanghai Jiao Tong University (2008-2011) as a Changjiang Chair Professor. He received a B.S. degree in electrical engineering and an M.S. degree in systems engineering from Dalian University of Technology, Dalian, China. He received his Ph.D. degree in systems engineering from Case Western Reserve University, Cleveland, Ohio, USA. His current research interests include neural networks and their applications. He published about 150 journal papers, 12 book chapters, 10 edited books, and numerous conference papers in these areas. He has been an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics Part B since 2003 and a member of the Editorial Advisory Board of the International Journal of Neural System since 2006. He also served as an Associate Editor of the IEEE Transactions on Neural Networks (1999-2009) and IEEE Transactions on Systems, Man, and Cybernetics Part C (2002-2005). He is an IEEE Fellow, an IEEE Distinguished Lecturer, and a recipient of the Outstanding Paper Award for a paper published in the IEEE Transactions on Neural Networks in 2008, Research Excellence Award from the Chinese University of Hong Kong for 2008-2009 and Shanghai Natural Science Award (first class) in 2009.

12  

Plenary Talk

Evolving, Training and Designing Neural Network Ensembles Xin Yao

University of Birmingham, UK

Abstract

Combining neural and evolutionary computation has always been an interesting research topic, as learning and evolution are two fundamental forms of adaptation in Nature. Previous work on evolving neural networks has focused on single neural networks. However, monolithic neural networks are often too complex to train or evolve for large and complex problems. It is usually better to design a collection of simpler neural networks that work cooperatively to solve a large and complex problem, which reflects the common problem solving strategy of "divide-and-conquer". The key issue here is how to design such a collection automatically so that it has the best generalisation in learning. This talk introduces some work on evolving neural network ensembles, negative correlation learning, and multi-objective approaches to ensemble learning. The links among different learning algorithms are discussed. Online/incremental learning using ensembles will also be mentioned briefly. Relevant background papers to this talk can be found from http://www.cs.bham.ac.uk/~xin/journal_papers.html.

Biography

Xin Yao is a Professor (Chair) of Computer Science at the University of Birmingham, UK. He is the Director of CERCIA (the Centre of Excellence for Research in Computational Intelligence and Applications), University of Birmingham, UK, and of the Joint USTC-Birmingham Research Institute of Intelligent Computation and Its Applications. He is an IEEE Fellow and a Distinguished Lecturer of IEEE Computational Intelligence Society (CIS). He won the 2001 IEEE Donald G. Fink Prize Paper Award, IEEE Transactions on Evolutionary Computation Outstanding 2008 Paper Award, and many other best paper awards. He was a Changjian Chair Professor, a Distinguished Visiting Professor (Grand Master Chair Professorship) of University of Science and Technology of China (USTC) in Hefei, and a Distinguished Visiting Professor of Yuan Ze University, Taiwan. In his spare time, he volunteered as the Editor-in-Chief (2003.08) of IEEE Transactions on Evolutionary Computation and Vice President for Publications of the IEEE CIS (2009.12). He has been invited to give more than 60 keynote/plenary speeches at international conferences in many different countries. His major research interests include evolutionary computation, neural network ensembles, and their applications. He has more than 350 refereed publications in international journals and conferences.

13  

Plenary Talk

EvoSpike: Evolving Probabilistic Spiking Neural Networks and Neuro-Genetic Systems for Spatio- and Spectro-Temporal Data Modelling and Pattern

Recognition Nikola Kasabov

Auckland University of Technology, New Zealand

Abstract

Spatio- and spectro-temporal data (SSTD) are the most common data in many domain areas, including bioinformatics, neuroinformatics, ecology, environment, medicine, engineering, economics, etc. Still there are no sufficient methods to model such data and to discover complex spatio-temporal patterns from it. The brain is functioning as a spatio-temporal information processing machine and brilliantly deals with spatio-temporal data, thus being a natural inspiration for the development of new methods for SSTD. This research aims at the development of new methods for modeling and pattern recognition of SSTD, called evolving probabilistic spiking neural networks (epSNN), along with their applications.

epSNN are built on the principles of evolving connectionist systems and eSNN in particular and on probabilistic neuronal models. The latter extent the popular leaky integrate-and-fire spiking model with the introduction of some biologically plausible probabilistic parameters. The epSNN are evolving structures that learn and adapt to new incoming data in a fast incremental way.

The presented research explores several approaches to creating epSNN for SSTD, from a single neuron, to reservoir computing and neuro-genetic systems. The presented research explores further ensembles of neurons and neuronal structures that may be called 'reservoirs'. Here they are recurrent SNN that are evolving and deep learning structures, capturing spatial- and temporal components in their interaction and integration.

A main problem in the EvoSpike model and system development is the optimization of numerous parameters. For this purpose three approaches are proposed: using evolutionary computation methods; using a gene regulatory network (GRN) model, or using both in one system, depending on the application.

Biography Professor Nikola Kasabov, FIEEE, FRSNZ is the Director of the Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland. He holds a Chair of Knowledge Engineering at the School of Computing and Mathematical Sciences at Auckland University of Technology. Currently he is an EU FP7 Marie Curie Visiting Professor at the Institute of Neuroinformatics, ETH and University of Zurich. Kasabov is a Past President of the International Neural Network Society (INNS) and also of the Asia Pacific Neural Network Assembly (APNNA). He is a member of several technical committees of IEEE Computational Intelligence Society and a Distinguished Lecturer of the IEEE CIS. He has served as Associate Editor of Neural Networks, IEEE TrNN, IEEE TrFS, Information Science, J. Theoretical and Computational Nanosciences, Applied Soft Computing and other journals. Kasabov holds MSc and PhD from the Technical University of Sofia, Bulgaria. His main research interests are in the areas of neural networks, intelligent information systems, soft computing, bioinformatics, neuroinformatics. He has published more than 450 publications that include 15 books, 130 journal papers, 60 book chapters, 28 patents and numerous conference papers. He has extensive academic experience at various academic and research organisations in Europe and Asia. Prof. Kasabov has received the AUT VC Individual Research Excellence Award (2010), Bayer Science Innovation Award (2007), the APNNA Excellent Service Award (2005), RSNZ Science and Technology Medal (2001), and others. He is an Invited Guest Professor at the Shanghai Jiao Tong University (2010-2012). More information of Prof. Kasabov can be found on the KEDRI web site: http://www.kedri.info

13  

14  

ICONIP2011 Technical Program

Mon., Nov. 14

08:00-8:15 Opening Ceremony

Room: Banquet A Hall

Chair: Bao-liang Lu

08:15-9:15

Keynote Speech: Prof. Shun-ichi Amari,

Stable and Fast Decision by Neural Networks:

Fundamental Problems in Mathematical

Neuroscience

Room: Banquet A Hall

Chair: Liqing Zhang

09:15-10:15

Plenary Talk: Prof. Kunihiko Fukushima,

Recent Advances in the Neocognitron: Robust

Recognition of Visual Patterns

Room: Banquet A Hall

Chair: James Kwok

13:30-14:30

Plenary Talk: Prof. Lei Xu,

Automatic Model Selection During Learning:

A Comparative Overview

Room: Banquet A Hall

Chair: Akira Hirose

14:30-15:30

Plenary Talk: Prof. Soo-Young Lee,

Implicit Intention Recognition & Hierarchical

Knowledge Development for Artificial

Cognitive Systems

Room: Banquet A Hall

Chair: Kevin Wong

Tues., Nov. 15

08:00-9:00

Plenary Talk: Prof. Aike Guo,

Dopamine reveals neural circuit mechanisms of

value based decision making in fruit fly’s brain

Room: Banquet A Hall

Chair: Tom Gedeon

09:00-10:00

Plenary Talk: Prof. DeLiang Wang，

A Classification Approach to the Cocktail Party

Problem

Room: Banquet A Hall

Chair: Minho Lee

13:30-14:30

Plenary Talk: Prof. Derong Liu,

Self-Learning Control of Nonlinear Systems

based on Iterative Adaptive Dynamic

Programming Approach

Room: Banquet A Hall

Chair: Irwin King

14:30-15:30

Plenary Talk: Prof. Jun Wang,

The State of the Art of Neurodynamic

Optimization

Room: Banquet A Hall

Chair: Hongtao Lu

Wed., Nov. 16

08:00-9:00

Plenary Talk: Prof. Xin Yao,

Evolving, Training and Designing Neural

Network Ensembles

Room: Banquet A Hall

Chair: Andrew Chi-Sing

Leung

09:00-10:00

Plenary Talk: Prof. Nikola Kasabov,

EvoSpike: Evolving Probabilistic Spiking

Neural Networks and Neuro-Genetic Systems

for Spatio- and Spectro-Temporal Data

Modelling and Pattern Recognition

Room: Banquet A Hall

Chair: Noboru Ohnishi

15  

Mon., Nov. 14 MMA: Speech and Auditory Processing,

Room: Marseilles Hall Chair: Shuichi Kurogi

10:45 -11:00 Speaker Identification Using Discriminative

Learning of Large Margin GMM

Khalid Daoudi, Reda Jourani,

Régine André-Obrecht, Driss

Aboutajdine

11:00 -11:15

Preprocessing of Independent Vector Analysis

Using Feed-Forward Network for Robust Speech

Recognition

Myungwoo Oh, Hyung-Min Park

11:15 -11:30

Perfermances Evaluation of GMM-UBM and

GMM-SVM for Speaker Recognition in Realistic

World

Nassim Asbai, Abderrahmane

Amrouche, Mohamed Debyeche

11:30 -11:45 Naive Bayesian Multistep Speaker Recognition

Using Competitive Associative Nets

Shuichi Kurogi,Mineishi Shota,

Tsukazaki Tomohiro, Nishida

Takashi

11:45 -12:00 Modular Scale-Free Function Subnetworks in

Auditory Areas Sanming Song, Hongxun Yao

Mon., Nov. 14

MMB: Natural Language Processing and

Intelligent Web Information Processing,

Room: Sydney Hall

Chair: Rui-Feng Xu

10:45 -11:00 Using Hybrid Kernel Method for Question

Classification in CQA

Shixi Fan, Xiaolong Wang, Xuan

Wang, Xiaohong Yang

11:00 -11:15 News Thread Extraction based on Topical N-gram

Model with a Background Distribution Zehua Yan, Fang Li

11:15 -11:30 Diversifying Question Recommendations in

Community-based Question Answering

Yaoyun Zhang, Xiaolong Wang,

Xuan Wang, Ruifeng Xu, Buzhou

Tang

11:30 -11:45 User Identification for Instant Messages Yuxin Ding, Xuejun Meng,

Guangren Chai, Yan Tang

11:45 -12:00 Towards Understanding Spoken Tunisian Dialect Marwa Graja, Maher Jaoua,

Lamia Hadrich Belguith

Mon., Nov. 14 MMC: Bio-Medical Data Analysis

Room: Leeds Hall Chair: Jie Yang

10:45 -11:00

Dynamic Bayesian Network Modeling of

Cyanobacterial Biological Processes via Gene

Clustering

Nguyen Xuan Vinh, Madhu

Chetty, Ross Coppel , Pramod P.

Wangikar

11:00 -11:15 A Quasi-linear Approach for Microarray Missing

Value Imputation Yu Cheng, Lan Wang, Jinglu Hu

16  

11:15 -11:30 Knowledge-based Segmentation of Spine and Ribs

from Bone Scintigraphy

Qiang Wang, Qingqing Chang,

Yu Qiao, Yuyuan Zhu, Gang

Huang, Jie Yang

11:30 -11:45 Adaptive Region Growing Based on Boundary

Measures Yu Qiao, Jie Yang

11:45 -12:00

Exploring Associations Between Changes in

Ambient Temperature and Stroke Occurrence:

Comparative Analysis Using Global and

Personalised Modelling Approaches

Wen Liang, Yingjie Hu, Nikola

Kasabov, Valery Feigin

Mon., Nov. 14 MMD: Neural Coding and Learning

Room: Vienna Hall Chair: Tibor Bosse

10:45 -11:00

Dreaming Your Fear Away: A Computational

Model for Fear Extinction Learning During

Dreaming

Jan Treur

11:00 -11:15 On Rationality of Decision Models Incorporating

Emotion-Related Valuing and Hebbian Learning Jan Treur, Muhammad Umair

11:15 -11:30 Simple Models for Synaptic Information IntegrationDanke Zhang, Yuwei Cui,

Yuanqing Li, Si Wu

11:30 -11:45

A Modified Multiplicative Update Algorithm for

Euclidean Distance-Based Nonnegative Matrix

Factorization and its Global Convergence

Ryota Hibi, Norikazu Takahashi

11:45 -12:00 A Generalized Subspace Projection Approach for

Sparse Representation Classification Bingxin Xu, Ping Guo

Mon., Nov. 14

MME: Brain-Realistic Models for Learning,

Memory and Embodied Cognition

Room: Lyon Hall

Chair: Huajin Tang

10:45 -11:00 Brain Inspired Cognitive System for Learning and

Memory Huajin Tang, Weiwei Huang

11:00 -11:15 Axonal Slow Integration Induced Persistent Firing

Neuron Model

Ning Ning, Kaijun Yi, Kejie

Huang, Luping Shi

11:15 -11:30 A Neuro-Cognitive Robot for Spatial Navigation Weiwei Huang, Huajin Tang, Jiali

Yu, Chin Hiong Tan

11:30 -11:45 Associative Memory Model of Hippocampus CA3

Using Spike Response Neurons

Chin Hiong Tan, Eng Yeow

Cheu, Jun Hu, Qiang Yu, Huajin

Tang

11:45 -12:00 Goal-oriented Behavior Generation for

Visually-guided Manipulation Task

Sungmoon Jeong, Yunjung Park,

Hiroaki Arie, Jun Tani, Minho

Lee

17  

Mon., Nov. 14 MAA: Image Processing

Room: Marseilles Hall Chair: Yasuomi D. Sato

16:00 -16:15 A Multimodal Information Collector for

Content-Based Image Retrieval System

He Zhang, Mats Sjöberg, Jorma

Laaksonen, Erkki Oja

16:15 -16:30 Contour-Based Large Scale Image Retrieval Rong Zhou, Liqing Zhang

16:30 -16:45

Multiview Range Image Registration Using

Competitive Associative Net and

Leave-One-Image-Out Cross-Validation Error

Shuichi Kurogi, Tomokazu Nagi,

Shoichi Yoshinaga, Hideaki

Koya, Takeshi Nishida

16:45 -17:00 Airport Detection in Remote Sensing Images Based

on Visual Attention

Xin Wang, Bin Wang, Liming

Zhang

17:00 -17:15 Learning Global and Local Features for License

Plate Detection

Sheng Wang, Wenjing Jia, Qiang

Wu, Xiangjian He, Jie Yang

17:15 -17:30 Integrating Local Features into Discriminative

Graphlets for Scene Classification

Luming Zhang, Wei Bian, Mingli

Song, Dacheng Tao, Xiao Liu

17:30 -17:45 Decision Tree Based Recognition of Bangla Text

from Outdoor Scene Images

Ranjit Ghoshal, Anandarup Roy,

Tapan Kumar Bhowmik, Swapan

K. Parui

17:45 -18:00 A Markov Random Field Model for Image

Segmentation Based on Gestalt Laws

Yuan Ren, Huixuan Tang, Hui

Wei

Mon., Nov. 14

MAB: Biologically Inspired Vision and

Recognition

Room: Sydney Hall

Chair: Jun Miao

16:00 -16:15 Visual Reconstructed Representations for Object

Recognition and Detection

Yasuomi D. Sato, Yasutaka

Kuriya, Christoph von der

Malsburg

16:15 -16:30 Visual Cortex Inspired Junction Detection Shuzhi Sam Ge, Chengyao Shen,

Hongsheng He

16:30 -16:45 Skull-Closed Autonomous Development Yuekai Wang, Xiaofeng Wu,

Juyang Weng

16:45 -17:00 Analysis of The Proton Mediated Feedback Signals

in The Outer Plexiform Layer of Goldfish Retina

Nilton Liuji Kamiji, Masahiro

Yamada, Kazunori Yamamoto,

Hajime Hirasawa, Makoto

Kurokawa, Shiro Usui

17:00 -17:15 Saliency Detection Based on Scale Selectivity of

Human Visual System

Fang Fang, Laiyun Qing, Jun

Miao, Xilin Chen, Wen Gao

17:15 -17:30 A Saliency Detection Model based on Local and

Global Kernel Density Estimation

Huiyun Jing, Xin He, Qi

Han,Xiamu Niu

18  

17:30 -17:45 Bio-Inspired Visual Saliency Detection and Its

Application on Image Retargeting

Lijuan Duan, Chunpeng Wu,

Haitao Qiao, Jili Gu, Jun Miao,

Laiyun Qing, Zhen Yang

17:45 -18:00 Effects of Second-Order Statistics on Independent

Component Filters

Andre Cavalcante, Barros Allan

Kardec,Takeuchi Yoshinori,

Ohnishi Noboru

Mon., Nov. 14 MAC: Kernel Methods

Room: Leeds Hall Chair: Mehmet Gonen

16:00 -16:15 Multitask Learning Using Regularized Multiple

Kernel Learning

Mehmet Gönen, Melih Kandemir,

Samuel Kaski

16:15 -16:30 Multi-task Low-rank Metric Learning Based on

Common Subspace

Peipei Yang, Kaizhu Huang,

Cheng-Lin Liu

16:30 -16:45 On Low-Rank Regularized Least Squares for

Scalable Nonlinear Classification

Zhouyu Fu, Guojun Lu, Kai-Ming

Ting, Dengsheng Zhang

16:45 -17:00 Relational Extensions of Learning Vector

Quantization

Barbara Hammer, Frank-Michael

Schleif, Xibin Zhu

17:00 -17:15 Multi-Sphere Support Vector Clustering

Trung Le, Dat Tran, Phuoc

Nguyen, Wanli Ma, Dharmendra

Sharma

17:15 -17:30 Learning with Box Kernels Stefano Melacci, Marco Gori

17:30 -17:45 Solving Support Vector Machines Beyond Dual

Programming Xun Liang

17:45 -18:00 Support Constraint Machines Gori Marco, Melacci Stefano

Mon., Nov. 14

MAD: Unsupervised Learning and

Self-Organization

Room: Vienna Hall

Chair: Kunihiko Fukushima

16:00 -16:15 Neocognitron Trained by Winner-Kill-Loser with

Triple Threshold

Kunihiko Fukushima, Isao

Hayashi, and Jasmin Léveillé

16:15 -16:30 Shape Space Estimation by SOM² Sho Yakushiji, Tetsuo Furukawa

16:30 -16:45 The Self-Organizing Map Tree (SOMT) for

Nonlinear Data Causality Prediction

Younjin Chung, Masahiro

Takatsuka

16:45 -17:00 Simultaneous Pattern and Variable Weighting

During Topological Clustering

Nistor Grozavu and Younes

Bennani

17:00 -17:15 A Robust Approach for Multivariate Binary

Vectors Clustering and Feature Selection

Mohamed Al Mashrgy, Nizar

Bouguila, Khalid Daoudi

19  

17:15 -17:30 Co-clustering under Nonnegative Matrix

Tri-Factorization Lazhar Labiod, Mohamed Nadif

17:30 -17:45 A New Simultaneous Two-Levels Coclustering

Algorithm for Behavioural Data-Mining

Guénaël Cabanes, Younès

Bennani, Dominique Fresneau

17:45 -18:00

A Dynamic Unsupervised Laterally Connected

Neural Network Architecture for Integrative Pattern

Discovery

Asanka Fonseka, Damminda

Alahakoon, Jayantha Rajapakse

Mon., Nov. 14

MAE: Neural Network Models and

Applications

Room: Lyon Hall

Chair: John Sum

16:00 -16:15 Self-Adjusting Feature Maps Network Chin-Teng Lin, Dong-Lin Li,

Jyh-Yeong Chang

16:15 -16:30 Analysis On Wang's kWTA with Stochastic Output

Nodes

John Sum, Chi-sing Leung, Kevin

Ho

16:30 -16:45 Method of Solving Combinatorial Optimization

Problems with Stochastic Effects

Takahiro Sota, Yoshihiro

Hayakawa, Shigeo Sato, Koji

Nakajima

16:45 -17:00 Recall Time Reduction of A Morphological

Associative Memory Employing A Reverse Recall Hidetaka Harada, Tsutomu Miki

17:00 -17:15

Robust Control of Nonlinear System Using

Difference Signals and Multiple Competitive

Associative Nets

Shuichi Kurogi, Hiroshi Yuno,

Takeshi Nishida, Weicheng

Huang

17:15 -17:30 An Automated System for The Analysis of The

Status of Road Safety Using Neural Networks Brijesh Verma, David Stockwell

17:30 -17:45 Deep Belief Networks For Financial Prediction Bernardete Ribeiro, Noel Lopes

17:45 -18:00 An Information Theoretic Approach to Joint

Approximate Diagonalization

Matsuda Yoshitatsu, Yamaguchi

Kazunori

Tues., Nov. 15

TMA: Computational-Intelligent Human

Computer Interaction

Room: Marseilles Hall

Chair: Jyh-Yeong Chang

10:30 -10:45 An EEG-Based Brain-Computer Interface for Dual

Task Driving Detection

Chin-Teng Lin,Yu-Kai Wang,

Shi-An Chen

10:45 -11:00 A Sparse Common Spatial Pattern Algorithm for

Brain-Computer Interface

Li-Chen Shi, Yang Li, Rui-Hua

Sun, Bao-Liang Lu

11:00 -11:15 EEG-based Motion Sickness Estimation Using

Principal Component Regression

Li-Wei Ko, Chun-Shu Wei,

Shi-An Chen, Chin-Teng Lin

11:15 -11:30 Reading Your Mind: EEG During Reading Task Tan Vo, Tom Gedeon

11:30 -11:45 A Novel Combination of Time Phase and EEG

Frequency Components for SSVEP-based BCI Jing Jin, Yu Zhang, Xingyu Wang

20  

11:45 -12:00 Generalised Support Vector Machine for

Brain-Computer Interface

Trung Le, Dat Tran, Tuan Hoang,

Wanli Ma, Dharmendra Sharma

Tues., Nov. 15

TMB: Human-Originated Data Analysis and

Implementation

Room: Sydney Hall

Chairs: Hyeyoung Park,

Sang-Woo Ban

10:30 -10:45 A Robust Face Recognition through Statistical

Learning of Local Features Jeongin Seo, Hyeyoung Park

10:45 -11:00 Adaptive Colour Calibration for Object Tracking

under Spatially-Varying Illumination Environments

Heesang Shin, Napoleon H.

Reyes, Andre L. Barczak

11:00 -11:15 Expanding Konwledge Source with Ontology

Alignment for Augmented Cognition

Jeong-Woo Son, Seongtaek Kim,

Seong-Bae Park, Yunseok Noh,

Jun-Ho Go

11:15 -11:30 Nyström Approximations for Scalable Face

Recognition: A Comparative Study Jeong-Min Yun, Seungjin Choi

11:30 -11:45 Development of Visualizing Earphone and Hearing

Glasses for Human Augmented Cognition

Byunghun Hwang, Cheol-Su

Kim, Hyung-Min Park, Yun-Jung

Lee, Min-Young Kim, Minho Lee

11:45 -12:00 An Online Human Activity Recognizer for Mobile

Phones with Accelerometer

Yuki Maruno, Kenta Cho, Yuzo

Okamoto, Hisao Setoguchi,

Kazushi Ikeda

Tues., Nov. 15 TMC: Clifford Algebraic Neural Networks

Room: Leeds Hall Chair: Yasuaki Kuroe

10:30 -10:45

Comparison of Complex- and Real-valued

Feedforward Neural Networks in Their

Generalization Ability

Akira Hirose, Shotaro Yoshida

10:45 -11:00 Widely Linear Processing of Hypercomplex Signals Tohru Nitta

11:00 -11:15 An Automatic Music Transcription Based on

Translation of Spectrum and Sound Path EstimationRyota Ikeuchi, Kazushi Ikeda

11:15 -11:30 Real-Time Hand Gesture Recognition Using

Complex-Valued Neural Network (CVNN)

Abdul Rahman Hafiz, Md Faijul

Amin, Kazuyuki Murase

11:30 -11:45

Wirtinger Calculus Based Gradient Descent and

Levenberg-Marquardt Learning Algorithms in

Complex-Valued Neural Networks

Md. Faijul Amin, Muhammad

Ilias Amin, A.Y.H. Al-Nuaimi,

and Kazuyuki Murase

11:45 -12:00 Models of Hopfield-type Cliford Neural Networks

and Their Energy Functions

Yasuaki Kuroe, Shinpei

Tanigawa, Hitoshi Iima

Tues., Nov. 15 TMD: Multi-Agent Systems

Room: Vienna Hall Chair: Yun Li

21  

10:30 -10:45 A Computational Agent Model for Hebbian

Learning of Social Interaction Jan Treur

10:45 -11:00 The Bystander Effect: Agent-Based Simulation of

People's Reaction to Norm Violation Charlotte Gerritsen

11:00 -11:15 Multi Agent Carbon Trading Incorporating Human

Traits and Game Theory

Long Tang, Suryani Lim, Madhu

Chetty

11:15 -11:30 Q-Learning with Double Progressive Widening :

Application to Robotics

Nataliya Sokolovska, Olivier

Teytaud, Mario Milone

11:30 -11:45

An Action Selection Method Based on Estimation

of Other's Intention in Time-Varying Multi-Agent

Environments

Kunikazu Kobayashi, Ryu

Kanehira, Takashi Kuremoto,

Masanao Obayashi

11:45 -12:00

Analysis of Beliefs of Survivors of the 7/7 London

Bombings Application of a Formal Model for

Contagion of Mental States

Tibor Bosse, Vikas Chandra, Eve

Mitleton-Kelly, C. Natalie van der

Wal

Tues., Nov. 15 TME: Supervised Learning

Room: Lyon Hall

Chairs: Yoshifusa Ito,

Simone Fiori

10:30 -10:45 Regularizer for Co-existing of Open Weight Fault

and Multiplicative Weight Noise

Chi-Sing Leung, John Pui-Fai

Sum

10:45 -11:00 Uncertainty Measure for Selective Sampling Based

on Class Probability Output Networks

Ho Gyeong Kim, Rhee Man Kil,

Soo-Young Lee

11:00 -11:15 A New Algorithm for Learning Mahalanobis

Discriminant Functions by a Neural Network

Yoshifusa Ito, Hiroyuki Izumi,

Cidambi Srinivasan

11:15 -11:30 An Incremental Class Boundary Preserving

Hypersphere Classifier Noel Lopes, Bernardete Ribeiro

11:30 -11:45 An Extended TopoART Network for the Stable

On-Line Learning of Regression Functions Marko Tscherepanow

11:45 -12:00

Statistical Nonparametric Bivariate Isotonic

Regression by Look-Up-Table-Based Neural

Networks

Simone Fiori

Tues., Nov. 15 TAA: Spiking Neurons

Room: Marseilles Hall Chair: Nikola Kasabov

16:00 -16:15 Evolving Probabilistic Spiking Neural Networks for

Spatio-Temporal Pattern Recognition

Nikola Kasabov, Kshitij Dhoble,

Nuttapod Nuntalid, Ammar

Mohemmed

16:15 -16:30 Event-Driven Simulation of Arbitrary Spiking

Neural Networks on SpiNNaker

Thomas Sharp, Luis A. Plana,

Francesco Galluppi, Steve Furber

16:30 -16:45 Dynamic Response Behaviors of A Generalized

Asynchronous Digital Spiking Neuron Model

Takashi Matsubara, Hiroyuki

Torikai

22  

16:45 -17:00 A New Learning Algorithm for Adaptive Spiking

Neural Networks

J Wang, A Belatreche, L.P.

Maguire, T.M. McGinnity

17:00 -17:15 Reservoir-based Evolving Spiking Neural Network

for Spatio-Temporal Pattern Recognition

Stefan Schliebs, Haza Nuzly

Abdull Hamed, Nikola Kasabov

17:15 -17:30

Generalized PWC Analog Spiking Neuron Model

and Reproduction of Fundamental

Neurocomputational Properties

Yutaro Yamashita, Hiroyuki

Torikai

17:30 -17:45 Nonlinear Effect on Phase Response Curve of

Neuron Model

Munenori Iida, Toshiaki Omori,

Toru Aonishi, Masato Okada

17:45 -18:00 Self-organizing Digital Spike Interval Maps Takashi Ogawa, Toshimichi Saito

18:00-18:15 SPAN: A Neuron for Precise-Time Spike Pattern

Association

Ammar Mohemmed, Stefan

Schliebs, Nikola Kasabov

Tues., Nov. 15 TAB: Combining Multiple Learners

Room: Sydney Hall Chair: Nistor Grozavu

16:00 -16:15 Unsupervised Object Ranking Using Not Even

Weak experts

Antoine Cornuéjols, Christine

Martin

16:15 -16:30 Weighted Topological Clustering for Categorical

Data

Nicoleta Rogovschi, Mohamed

Nadif

16:30 -16:45 An Evolutionary Algorithm Based Optimization of

Neural Ensemble Classifiers Chien-Yuan Chiu, Brijesh Verma

16:45 -17:00 Using Bagging and Cross-Validation to Improve

Ensembles Based on Penalty Terms

Joaquín Torres-Sospedra, Carlos

Hernández-Espinosa, Mercedes

Fernández-Redondo

17:00 -17:15 Feature Relationships Hypergraph for Multimodal

Recognition

Luming Zhang, Mingli Song, Wei

Bian , Dacheng Tao, Xiao Liu,

Jiajun Bu, Chun Chen

17:15 -17:30 Energy-Based Feature Selection and Its Ensemble

Version Yun Li, Su-Yan Gao

17:30 -17:45 Improving Boosting Methods by Generating

Specific Training and Validation Sets

Joaquín Torres-Sospedra, Carlos

Hernández-Espinosa, Mercedes

Fernández-Redondo

17:45 -18:00 Predicting Concept Changes Using a Committee of

Experts

Ghazal Jaber, Antoine

Cornuéjols , Philippe Tarroux

Tues., Nov. 15 TAC: Brain Signal Processing

Room: Leeds Hall Chair: Jianting Cao

16:00 -16:15 A Novel Oddball Paradigm for Affective BCIs

using Emotional Faces as Stimuli

Qibin Zhao,Akinari Onishi, Yu

Zhang, Jianting Cao,Liqing

Zhang, Andrzej Cichocki

23  

16:15 -16:30

Multiway Canonical Correlation Analysis for

Frequency Components Recognition in

SSVEP-based BCIs

Yu Zhang,Guoxu Zhou,Qibin

Zhao, Akinari Onishi, Jing Jin,

Xingyu Wang, Andrzej Cichocki

16:30 -16:45

An Emotional Face Evoked EEG Signal

Recognition Method Based on Optimal EEG

Feature and Electrodes Selection

Lijuan Duan,Xuebin Wang, Zhen

Yang, Haiyan Zhou, Chunpeng

Wu, Qi Zhang, Jun Miao

16:45 -17:00

Functional Connectivity Analysis with Voxel-based

Morphometry for Diagnosis of Mild Cognitive

Impairment

JungHoe Kim, Jong-Hwan Lee

17:00 -17:15 An Application of Translation Error to Brain Death

Diagnosis Gen Hori, Jianting Cao

17:15 -17:30

Research on Relationship Between Saccadic Eye

Movements and EEG Signals in the Case of Free

Movements and Cued Movements

Arao Funase, Andrzej Cichocki,

and Ichi Takumi

17:30 -17:45

Classification of Multi-spike Trains and Its

Application in Detecting Task Relevant Neural

Cliques

Fanxing Hu, Bao-Ming Li, Hui

Wei

17:45 -18:00

EEG Classification with BSA Spike Encoding

Algorithm and Evolving Probabilistic Spiking

Neural Network

Nuttapod Nuntalid, Kshitij

Dhoble, Nikola Kasabov

Tues., Nov. 15

TAD: Computational Advances in

Bioinformatics

Room: Vienna Hall

Chair: Jonathan H. Chan

16:00 -16:15

Pathway-Based Microarray Analysis with

Negatively Correlated Feature Sets for Disease

Classification

Pitak Sootanan, Santitham

Prom-on, Asawin Meechai, and

Jonathan H. Chan

16:15 -16:30 A Feature Selection Approach for Emulating the

Structure of Mental Representations

Marko Tscherepanow, Marco

Kortkamp, Sina Kühnel, Jonathan

Helbach, Christoph Schütz,

Thomas Schack

16:30 -16:45 A Modified Two-Stage SVM-RFE Model for

Cancer Classification Using Microarray Data

Phit Ling Tan, Shing Chiang Tan,

Chee Peng Lim, Swee Eng Khor

16:45 -17:00

Improved Gene Clustering Based on Particle

Swarm Optimization, K-Means, and Cluster

Matching

Yau-King Lam, P.W.M. Tsang,

Chi-Sing Leung

17:00 -17:15 A Memetic Approach to Protein Structure

Prediction in Triangular Lattices

M.K. Islam, M. Chetty, A. Dayem

Ullah, K. Steinhofel

17:15 -17:30 Personalised Modelling on SNPs Data for Crohn's

Disease Prediction Yingjie Hu, Nikola Kasabov

24  

17:30 -17:45 Research on Classification Methods of Glycoside

Hydrolases Mechanism Fan Yang, Lin Wang

17:45 -18:00

The Relationship between the Newborn Rats’

Hypoxic-ischemic Brain Damage and Heart Beat

Interval Information

Xiaomin Jiang, Hiroki Tamura,

Koichi Tanno, Li Yang, Hiroshi

Sameshima, Tsuyomu Ikenoue

Tues., Nov. 15 TAE: Graphical and Mixture Models

Room: Lyon Hall Chair: Kazushi Ikeda

16:00 -16:15 An Infinite Mixture of Inverted Dirichlet

Distributions Taoufik Bdiri and Nizar Bouguila

16:15 -16:30 Polynomial Time Algorithm for Learning Globally

Optimal Dynamic Bayesian Network

Nguyen Xuan Vinh, Madhu

Chetty, Ross Coppel, Pramod P.

Wangikar

16:30 -16:45 Human Activity Inference Using Hierarchical

Bayesian Network in Mobile Contexts Young-Seol Lee, Sung-Bae Cho

16:45 -17:00 Image Classification based on Weighted Topics Yunqiang Liu, Vicent Caselles

17:00 -17:15 Feature Reduction Using a Topic Model for the

Prediction of Type III Secreted Effectors Sihui Qi, Yang Yang, Anjun Song

17:15 -17:30 A Variational Statistical Framework for Object

Detection

Wentao Fan, Nizar Bouguila,

Djemel Ziou

17:30 -17:45 SVM and Greedy GMM Applied on Target

Identification

Dalila Yessad, Abderrahmane

Amrouche, Mohamed Debyeche

17:45 -18:00 Spatial Finite Non-Gaussian Mixture for Color

Image Segmentation Ali Sefidpour, Nizar Bouguila

Wed., Nov. 16 WMA: Brain-like Systems

Room: Marseilles Hall Chair: Minho Lee

10:30 -10:45

Implementation of Visual Attention System Using

Artificial Retina Chip and Bottom-up Saliency Map

Model

Bumhwi Kim, Hirotsugu Okuno,

Tetsuya Yagi, Minho Lee

10:45 -11:00 A Biologically Inspired Model for Occluded

Patterns Saifullah Mohammad

11:00 -11:15 Bio-inspired Model of Spatial Cognition Michal Vavrecka, Igor Farkas,

Lenka Lhotska

11:15 -11:30 Visual Information of Endpoint Position is Not

Required for Prism Adaptation of Shooting Task

Takumi Ishikawa, Yutaka

Sakaguchi

11:30 -11:45 Stable Fast Rewiring Depends on the Activation of

Skeleton Voxels Sanming Song, Hongxun Yao

25  

11:45 -12:00 A Method to Construct Visual Recognition

Algorithms on The Basis of Neural Activity Data

Hiroki Kurashige, Hideyuki

Cateau

Wed., Nov. 16

WMB: Integrating Multiple Nature-inspired

Approaches

Room: Sydney Hall

Chair: Xin Yao

10:30 -10:45

Fitness Landscape-based Parameter Tuning Method

for Evolutionary Algorithms for Computing Unique

Input Output Sequences

Jinlong Li, Guanzhou Lu, Xin

Yao

10:45 -11:00 Introducing the Mallows Model on Estimation of

Distribution Algorithms

Josu Ceberio, Alexander

Mendiburu, Jose A. Lozano

11:00 -11:15

A Hybrid Dynamic Multi-objective Immune

Optimization Algorithm Using Prediction Strategy

and Improved Differential Evolution Crossover

Operator

Yajuan Ma, Ruochen Liu,

Ronghua Shang

11:15 -11:30 Alleviate the Hypervolume Degeneration Problem

of NSGA- II Fei Peng, Ke Tang

11:30 -11:45 Optimizing Interval Multi-objective Problems

Using IEAs with Preference Direction

Jing Sun, Dunwei Gong, Xiaoyan

Sun

11:45 -12:00 Evolution of Neural Controllers for Emergence of

Leadership in Robot Colony

Seung-Hyun Lee, Si-Hyuk Yi,

Sung-Bae Cho

Wed., Nov. 16 WMC: Web and Document Processing

Room: Leeds Hall Chair: Irwin King

10:30 -10:45 Topic Modeling of Chinese Language Using

Character-Word Relations

Qi Zhao, Zengchang Qin, Tao

Wan

10:45 -11:00 Enrichment and Reductionism: Two Approaches

for Web Query Classification

Ritesh Agrawal, Xiaofeng Yu,

Irwin King, Remi Zajac

11:00 -11:15

Resource Allocation and Scheduling of Multiple

Composite Web Services in Cloud Computing

Using Cooperative Coevolution

Lifeng Ai, Maolin Tang, Colin

Fidge

11:15 -11:30 PatentRank: An Ontology-based Approach to

Patent Search

Ming Li, Hai-Tao Zheng, Yong

Jiang, Shu-Tao Xia

11:30 -11:45 Learning to Rank Documents Using Similarity

Information between Objects

Di Zhou, Yuxin Ding, Qingzhen

You, Min Xiao

11:45 -12:00 Effect of Dimensionality Reduction on Different

Distance Measures in Document Clustering

Mari-Sanna Paukkeri, Ilkka

Kivimaki, Santosh Tirunagari,

Timo Honkela

26  

Wed., Nov. 16

WMD: Advances in Computational

Intelligence Methods based Pattern

Recognition

Room: Vienna Hall

Chairs: Kaizhu Huang; Jun

Sun

10:30 -10:45 Graphical Lasso Quadratic Discriminant Function

for Character Recognition

Bo Xu, Kaizhu Huang, Irwin

King, Cheng-Lin Liua, Jun Sun,

Naoi Satoshi

10:45 -11:00 Learning Based Visibility Measuring with Images

Xu-Cheng Yin, Tian-Tian He,

Hong-Wei Hao, Xi Xu,

Xiao-Zhong Cao, Qing Li

11:00 -11:15 Enhanced Codebook Model for Real-time

Background Subtraction

Munir Shah, Jeremiah Deng,

Brendon Woodford

11:15 -11:30 Multi-View Pedestrian Recognition Using Shared

Dictionary Learning with Group Sparsity

Shuai Zheng, Bo Xie, Kaiqi

Huang, Dacheng Tao

11:30 -11:45 Denial-of-Service Attack Detection Based on

Multivariate Correlation Analysis

Zhiyuan Tan, Aruna Jamdagni,

Xiangjian He, Priyadarsi Nanda,

Ren Ping Liu

11:45 -12:00 A Two Stage Algorithm for K-mode Convolutive

Nonnegative Tucker Decomposition

Qiang Wu, Liqing Zhang, Andrzej

Cichocki

Wed., Nov. 16

WME: Brain Imaging and Brain-computer

Interfaces

Room: Lyon Hall

Chair: Liqing Zhang

10:30 -10:45 A Probabilistic Model for Discovering High Level

Brain Activities from fMRI Jun Li, Dacheng Tao

10:45 -11:00

An Integrated Hierarchical Gaussian Mixture

Model to Estimate Vigilance Level Based on EEG

Recordings

Jing-Nan Gu, Hong-Jun Liu,

Hong-Tao Lu, Bao-Liang Lu

11:00 -11:15 Power Laws for Spontaneous Neuronal Activity in

Hippocampal CA3 Slice Culture

Toshikazu Samura, Yasuomi D.

Sato, Yuji Ikegaya,Hatsuo

Hayashi

11:15 -11:30 Multifractal Analysis of Intracranial EEG in

Epilepticus Rats Tao Zhang, A Kunhan Xu

11:30 -11:45 P300 Response Classification in the Presence of

Magnitude and Latency Fluctuations

Wee Lih Lee, Yee Hong Leung,

Tele Tan

11:45 -12:00 EEG Analysis of the Navigation Strategies in a 3D

Tunnel Task

Michal Vavre cka, Vaclav Gerla,

Lenka Lhotska

27  

Wed., Nov. 16

(13:30-15:30）

Special Forum: Emerging Technologies

and Future Directions in Computational

Intelligence

Speakers: Shun-ichi Amari; Kunihiko

Fukushima; Nikola Kasabov; Soo-Young Lee;

Derong Liu; Jun Wang; and Xin Yao

Organizers: James Kwok

and Liqing Zhang;

Moderator: DeLiang Wang

Wed., Nov. 16 WP: Poster Session

15:30-17:30 Learning of Dynamic BNN toward

Storing-and-Stabilizing Periodic Patterns

Ryo Ito, Yuta Nakayama,

Toshimichi Saito

15:30-17:30 Margin Preserving Projection for Image Set Based

Face Recognition

Ke Fan, Wanquan Liu, Senjian

An, Xiaoming Chen

15:30-17:30 A Novel Neural Network for Solving Singular

Nonlinear Convex Optimization Problems

Lijun Liu, Rendong Ge, Pengyuan

Gao

15:30-17:30

Introducing Reordering Algorithms to Classic

Well-known Ensembles to Improve Their

Performance

Joaquín Torres-Sospedra, Carlos

Hernández-Espinosa, Mercedes

Fernández-Redondo

15:30-17:30 Nonlinear Nearest Subspace Classifier Li Zhang, Wei-Da Zhou, Bing Liu

15:30-17:30 A Novel Framework Based on Trace Norm

Minimization for Audio Event Detection

Ziqiang Shi, Jiqing Han, Tieran

Zheng

15:30-17:30 Making Image to Class Distance Comparable Deyuan Zhang, Bingquan Liu,

Chengjie Sun, Xiaolong Wang

15:30-17:30 Co-clustering for Binary Data with Maximum

Modularity Lazhar Labiod, Mohamed Nadif

15:30-17:30 Induction of the Common-sense Hierarchies in

Lexical Data

Julian Szymański, Wlodzislaw

Duch

15:30-17:30 A Novel Synthetic Minority Oversampling

Technique for Imbalanced Data Set Learning

Sukarna Barua, Md. Monirul

Islam, Kazuyuki Murase

15:30-17:30 An Evolutionary Fuzzy Clustering with Minkowski

Distances

Vivek Srivastava, Bipin K

Tripathi, Vinay K Pathak

15:30-17:30 Sparse Coding Image Denoising Based on Saliency

Map Weight Haohua Zhao, Liqing Zhang

15:30-17:30 Fast Growing Self Organizing Map for Text

Clustering

Sumith Matharage, Damminda

Alahakoon, Jayantha Rajapakse,

Pin Huang

15:30-17:30

Introducing a Novel Data Management Approach

for Distributed Large Scale Data Processing In

Future Computer Clouds

Amir H. Basirat, Asad I. Khan

28  

15:30-17:30 An Approach to Distance Estimation with Stereo

Vision Using Address-Event-Representation

D. M. M. Jesus, J. F. Angel, P. V.

Rafael, L. T. M. Ramon, C. E.

Elena, L. B. Alejandro, J. M.

Gabriel, M. E. Arturo

15:30-17:30 Estimation System for Human-Interest Degree

while Watching TV Commercials Using EEG

Yuna Negishi, Zhang Dou, Yasue

Mitsukura

15:30-17:30

Modulations of Electric Organ Discharge and

Representation of The Modulations on

Electroreceptors

Kazuhisa Fujita

15:30-17:30 Spiking Neural PID Controllers Andrew Webb, Sergio Davies,

David Lester

15:30-17:30 AER Spiking Neuron Computation on GPUs: the

Frame-to-AER generation

L.T. M. Ramon, D.R. Fernando,

D. M. M. Jesus, J. M. Gabriel, L.

B. Alejandro

15:30-17:30 Enhanced Discrimination of Face Orientation Based

on Gabor Filters

Hyun Ah Song, Sung-do Choi,

Soo-Young Lee

15:30-17:30 Conflict Resolution Based Global Search Operators

for Long Protein Structures Prediction

Md Kamrul Islam, Madhu Chetty,

and Manzur Murshed

15:30-17:30

Comparison Between the Applications of

Fragment-based and Vertex-based GPU

Approaches in K-Means Clustering of Time Series

Gene Expression Data

Yau-King Lam, Wuchao Situ,

P.W.M. Tsang, Chi-Sing Leung,

Yi Xiao

15:30-17:30 EEG-based Emotion Recognition Using Frequency

Domain Features and Support Vector Machines

Xiao-Wei Wang, Dan Nie,

Bao-Liang Lu

15:30-17:30

Research of EEG from Patients with Temporal

Lobe Epilepsy on Causal Analysis of Directional

Transfer Functions

Zhi-Jun Qiu, Hong-Yan Zhang,

Xin Tian

15:30-17:30 Adaptive Classification for Brain-Machine

Interface with Reinforcement Learning

Shuichi Matsuzaki, Yusuke

Shiina, Yasuhiro Wada

15:30-17:30

Person Identification using

Electroencephalographic Signals Evoked by Visual

Stimuli

Jia-Ping Lin, Yong-Sheng Chen,

Li-Fen Chen

15:30-17:30 Medial Axis for 3D Shape Representation Wei Qiu and Ko Sakai

15:30-17:30 Macro Features based Text Categorization Dandan Wang, Qingcai Chen,

Xiaolong Wang, Buzhou Tang

29  

15:30-17:30

Univariate Marginal Distribution Algorithm in

Combination with Extremal Optimization

(EO,GEO)

Mitra Hashemi, Mohammad Reza

Meybodi

15:30-17:30 Promoting Diversity in Particle Swarm

Optimization to Solve Multimodal Problems

Shi Cheng, Yuhui Shi, Quande

Qin

15:30-17:30 Analysis of Feature Weighting Methods Based on

Feature Ranking Methods for Classification

Norbert Jankowski, Krzysztof

Usowicz

15:30-17:30

Simultaneous Learning of Instantaneous and

Time-Delayed Genetic Interactions Using Novel

Information Theoretic Scoring Technique

Nizamul Morshed, Madhu Chetty,

Nguyen Xuan Vinh

15:30-17:30 Dynamic Complex-valued Associative Memory

with Strong Bias Terms

Yozo Suzuki, Michimasa Kitahara

and Masaki Kobayashi

15:30-17:30 Describing Human Identity Using Attributes

Zhuoli Zhou, Jiajun Bu, Dacheng

Tao, Luming Zhang, Mingli Song,

Chun Chen

15:30-17:30 Selective Track Fusion Li Xu, Peijun Ma, Xiaohong Su

15:30-17:30

Fast and Incremental Neural Associative Memory

Based Approach for Adaptive Open-loop Structural

Control in High-rise Buildings

Aram Kawewong, Yuji Koike,

Osamu Hasegawa, Fumio Sato

15:30-17:30 Emergence of Purposive and Grounded

Communication through Reinforcement Learning

Katsunari Shibata, Kazuki

Sasahara

15:30-17:30 Support Vector Machines with Weighted

Regularization

Tatsuya Yokota, Yukihiko

Yamashita

15:30-17:30 A Novel Parameter Refinement Approach to One

Class Support Vector Machine

Trung Le, Dat Tran, Wanli Ma,

Dharmendra Sharma

15:30-17:30

Testing Predictive Properties of Efficient Coding

Models with Synthetic Signals Modulated in

Frequency

Fausto Lucena, Mauricio Kugler,

Allan Kardec Barros, Noboru

Ohnishi

15:30-17:30 Utilization of A Virtual Patient Model to Enable

Tailored Therapy for Depressed Patients Fiemke Both, Mark Hoogendoorn

15:30-17:30 Adaptive Detection of Hotspots in Thoracic Spine

from Bone Scintigraphy

Qingqing Chang, Qiang Wang,

Yu Qiao, Yuyuan Zhu, Gang

Huang, Jie Yang

15:30-17:30 ICA-based Automatic Classification of PET Images

From ADNI database

Wenlu Yang, Fangyu He, Xinyun

Chen, Xudong Huang

15:30-17:30 Visual Analytics of Clinical and Genetic Datasets

of Acute Lymphoblastic Leukaemia

Nguyen Quang Vinh，Gleeson

Andrew, Ho Nicholas， Mao

Lin Huang，Simoff Simeon,

Catchpoole Daniel

30  

15:30-17:30 Discrimination of Protein Thermostability Based on

a New Integrated Neural Network Jingru Xu,Yuehui Chen

15:30-17:30 Complex Detection Based on Integrated Properties

Yang Yu， Lei Lin，Chengjie

Sun, Xiaolong Wang, Xuan

Wang

15:30-17:30 ECG Classification Using ICA Features and

Support Vector Machines Yang Wu, Liqing Zhang

15:30-17:30 Emotiono: an Ontology with Rule-Based Reasoning

for Emotion Recognition

Xiaowei Zhang, Bin Hu, Philip

Moore, Jing Chen, Lin Zhou

15:30-17:30 An Adaptive Approach to Chinese Semantic

Advertising

Jin-Yuan Chen, Hai-Tao Zheng,

Yong Jiang, Shu-Tao Xia

15:30-17:30 Scalable Data Clustering: A Sammon’s Projection

Based Technique for Merging GSOMs

Hiran Ganegedara, Damminda

Alahakoon

15:30-17:30 The Rough Set-based Algorithm for Two Steps Shu-Hsien Liao, Yin-Ju Chen,

Shiu-Hwei Ho

15:30-17:30 Multi-label Weighted k-Nearest Neighbor Classifier

with Adaptive Weight Estimation Jianhua Xu

15:30-17:30

Parallel Rough Set: Dimensionality Reduction and

Feature Discovery of Multi-Dimensional Data in

Visualization

Tze-Haw Huang, Mao Lin Huang,

Jesse S. Jin

15:30-17:30 Feature Extraction via Balanced Average

Neighborhood Margin Maximization

Xiaoming Chen, Wanquan Liu,

Jianhuang Lai, Ke Fan

15:30-17:30 Document Classification on Relevance: A Study on

Eye Gaze Patterns for Reading

Daniel Fahey, Tom Gedeon,

Dingyun Zhu

15:30-17:30 A Lightweight Ontology LearningMethod for

Chinese Government Documents

Xing Zhao, Hai-Tao Zheng, Yong

Jiang, Shu-Tao Xia

15:30-17:30 Relative Association Rules Based on Rough Set

Theory

Shu-Hsien Liao, Yin-Ju Chen,

Shiu-Hwei Ho

15:30-17:30

15:30-17:30 Use of A Sparse Structure to Improve Learning

Performance of Recurrent Neural Networks

Hiromitsu Awano, Shun Nishide,

Hiroaki Arie, Jun Tani, Toru

Takahashi, Hiroshi G. Okuno,

Tetsuya Ogata

15:30-17:30 Research on A RBF Neural Network in Stereo

Matching

Sheng Xu, Ning Ye, Fa Zhu,

Shanshan Xu, Liuliu Zhou

15:30-17:30 Stability Criterion of Discrete-time Recurrent

Neural Networks with Periodic Delays

Xing Yin, Weigen Wu, Qianrong

Tan

31  

15:30-17:30 Improved Global Robust Stability Criteria for

Delayed BAM Neural Networks Xiaolin Li, Ming Liu

15:30-17:30 High Order Hopfield Network with Self-feedback

to Solve Crossbar Switch Problem

Yuxin Ding, Li Dong, Bin Zhao,

Zhanjun Lu

15:30-17:30 Analyzing The Dynamics of Emotional Scene

Sequence Using Recurrent Neuro-Fuzzy Network Qing Zhang, Minho Lee

15:30-17:30 Geometry vs. Appearance for Discriminating

between Posed and Spontaneous Emotions

Ligang Zhang, Dian

Tjondronegoro, Vinod Chandran

15:30-17:30 Towards Learning Inverse Kinematics with A

Neural Network Based Tracking Controller

Tim Waegeman, Benjamin

Schrauwen

15:30-17:30 Color Image Segmentation Based on Blocks

Clustering and Region Growing

Haifeng Sima, Lixiong Liu, Ping

Guo

15:30-17:30 Speed Up Spatial Pyramid Matching Using Sparse

Coding with Affinity Propagation Algorithm Rukun Hu, Ping Guo

15:30-17:30

Analog-Digital Circuit for Motion Detection Based

on Vertebrate Retina and Its Application to Mobile

Robot

Kimihiro Nishio, Taiki Yasuda

15:30-17:30

A Motion Detection Model Inspired by

Hippocampal Function and Its FPGA

Implementation

Haichao Liang, Takashi Morie

15:30-17:30

Intelligent Video Surveillance System Using

Dynamic Saliency Map and Boosted Gaussian

Mixture Model

Wono Lee, Giyoung Lee,

Sang-Woo Ban, Ilkyun Jung,

Minho Lee

15:30-17:30 Recovery of Sparse Signal from An Analog

Network Model

Chi Sing Leung, John Sum,

Ping-Man Lam, A. G.

Constantinides

15:30-17:30 A VLSI Spiking Neural Network with Symmetric

STDP and Associative Memory Operation

Frank L. Maldonado Huayaney,

Hideki Tanaka, Takayuki Matsuo,

Takashi Morie, Kazuyuki Aihara

15:30-17:30 Three Dimensional Surface Temperature

Measurement System

Tao Li, Kikuhito Kawasue,

Satoshi Nagatomo

15:30-17:30 Weber’s Law Based Center-Surround Hypothesis

for Bottom-Up Saliency Detection

Lili Lin, Wenhui Zhou, Hua

Zhang

15:30-17:30 Multi-scale Image Analysis Based on Non-Classical

Receptive Field Mechanism Hui Wei, Qingsong Zuo, Bo Lang

15:30-17:30 A Hybrid FMM-CART Model for Fault Detection

and Diagnosis of Induction Motors

Manjeevan Seera, Chee Peng

Lim, Dahaman Ishak

15:30-17:30 Super Resolution of Text Image by Pruning Outlier Ziye Yan, Yao Lu, JianWu Li

32  

15:30-17:30 Opponent and Feedback: Visual Attention Captured

Senlin Wang, Mingli Song,

Dacheng Tao, Luming Zhang,

Jiajun Bu, Chun Chen

15:30-17:30 Depth from Defocus via Discriminative Metric

Learning

Qiufeng Wu, Kuanquan Wang,

Wangmeng Zuo, Yanjun Chen

15:30-17:30 Modeling Manifold Ways of Scene Perception Mengyuan Zhu, Bolei Zhou

15:30-17:30 Dynamic Template Based Online Event Detection Dandan Wang, Qingcai Chen,

Xiaolong Wang, Jiacai Weng

15:30-17:30

Removing Unrelated Features Based on Linear

Dynamical System for Motor-Imagery-Based

Brain-Computer Interface

Jie Wu, Li-Chen Shi, Bao-Liang

Lu

15:30-17:30 Efficient Semantic Kernel-based Text Classification

Using Matching Pursuit KFDA

Qing Zhang, Jianwu Li, Zhiping

Zhang

15:30-17:30 Facial Image Analysis Using Subspace Segregation

Based on Class Information Minkook Cho, Hyeyoung Park

15:30-17:30

A Recurrent Multimodal Network for Binding

Written Words and Sensory-Based Semantics into

Concepts

Andrew P. Papli nski, Lennart

Gustafsson, William M. Mount

15:30-17:30

Recognition of Human’s Implicit Intention Based

on an

Eyeball Movement Pattern Analysis

Young-Min Jang, Sangil Lee,

Rammohan Mallipeddi, Ho-Wan

Kwak, Minho Lee

15:30-17:30 Stress Classification for Gender Bias in Reading Nandita Sharma, Tom Gedeon

15:30-17:30 Vigilance Estimation Based on Statistic Learning

with One ICA Component of EEG Signal Hongbin Yu, Hongtao Lu

15:30-17:30 Multimodal Identity Verification Based on

Learning Face and Gait Cues

S.M.Emdad Hossain, Girija

Chetty