http://www.extreme-learning-machines.org/ELM2011

General Chair

Guang‐Bin Huang

Nanyang Technological University, Singapore

Program Chairs

Dianhui Wang

La Trobe University, Australia

ZhihongMan

Swinburne University of Technology Australia

Organization Chairs

Feilong Cao

China Jiliang University, China

Xi‐Zhao Wang

Hebei University, China

Advisory Committee

Tom Heskes

RadboudUniversity Nijmegen, Netherlands

Kay Chen Tan

National University of Singapore, Singapore

Michel Verleysen

Université catholique de Louvain, Belgium

Zong‐Ben Xu

Xi’anJiao Tong University, China

Local Arrangenment Chair

Yubo Yuan

China Jiliang University,China

Publicity Chairs

Amaury Lendasse

HelsinkiUniversity of Technology, Finland

Bao‐Liang Lu

Shanghai Jiao Tong University China

Yew‐Song Ong

Nanyang Technological University, Singapore

Kar‐Ann Toh

Yonsei University, Korea

Call for Papers

Extreme Learning Machine (ELM) has demonstrated its great potentiality of resolving regression and classification problems. ELM overcomes many challenges faced by other computational intelligence methods such as feedforward neural networks and support vector machines. ELM has much faster learning speed, is ease of implementation, and requires less human intervene. ELM has become one of a few important tools for the state-of-art large-scale computing and artificial intelligence.

This symposium will provide a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique. This symposium will be held in Hangzhou, China. Hangzhou is a key national tourism and historical city. Hangzhou is renowned as “Paradise on Earth.”

All the papers presented in this symposium will be published in special issues of some reputable ISI indexed international journals such as Neurocomputing and Soft Computing, etc. No additional symposium proceedings are provided.

Topics of interest:

All the submissions must be related to ELM technique. Topics of interest include but are not limited to:

Theories

• Universal approximation and convergence
• Robustness analysis
• Classification capability

Algorithms

• Real-time learning
• Sequential and incremental learning
• Kernel based algorithms

Applications

• Time series prediction
• Pattern recognition
• Internet applications
• Biometrics
• Bioinformatics
• Power systems
• Control engineering
• Human computer interface

Paper submission:

Only full length submissions with good quality will be considered to present  at this symposium. All the submissions will go through rigorous blind review.Details on manuscript submission will be given online http://www.extreme-learning-machines.org/ELM2011 by April 15, 2011.

Important dates:

Paper submission deadline: June 1, 2011

Notification of acceptance: September 1, 2011

Registration deadline: October 15, 2011

 http://www.extreme-learning-machines.org/ELM2011

http://www.extreme-learning-machines.org/ELM2011

General Chair

Guang‐Bin Huang

Nanyang Technological University, Singapore

Program Chairs

Dianhui Wang

La Trobe University, Australia

ZhihongMan

Swinburne University of Technology Australia

Organization Chairs

Feilong Cao

China Jiliang University, China

Xi‐Zhao Wang

Hebei University, China

Advisory Committee

Tom Heskes

RadboudUniversity Nijmegen, Netherlands

Kay Chen Tan

National University of Singapore, Singapore

Michel Verleysen

Université catholique de Louvain, Belgium

Zong‐Ben Xu

Xi’anJiao Tong University, China

Local Arrangenment Chair

Yubo Yuan

China Jiliang University,China

Publicity Chairs

Amaury Lendasse

HelsinkiUniversity of Technology, Finland

Bao‐Liang Lu

Shanghai Jiao Tong University China

Yew‐Song Ong

Nanyang Technological University, Singapore

Kar‐Ann Toh

Yonsei University, Korea

Call for Papers

Extreme Learning Machine (ELM) has demonstrated its great potentiality of resolving regression and classification problems. ELM overcomes many challenges faced by other computational intelligence methods such as feedforward neural networks and support vector machines. ELM has much faster learning speed, is ease of implementation, and requires less human intervene. ELM has become one of a few important tools for the state-of-art large-scale computing and artificial intelligence.

This symposium will provide a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique. This symposium will be held in Hangzhou, China. Hangzhou is a key national tourism and historical city. Hangzhou is renowned as “Paradise on Earth.”

All the papers presented in this symposium will be published in special issues of some reputable ISI indexed international journals such as Neurocomputing and Soft Computing, etc. No additional symposium proceedings are provided.

Topics of interest:

All the submissions must be related to ELM technique. Topics of interest include but are not limited to:

Theories

• Universal approximation and convergence
• Robustness analysis
• Classification capability

Algorithms

• Real-time learning
• Sequential and incremental learning
• Kernel based algorithms

Applications

• Time series prediction
• Pattern recognition
• Internet applications
• Biometrics
• Bioinformatics
• Power systems
• Control engineering
• Human computer interface

Paper submission:

Only full length submissions with good quality will be considered to present  at this symposium. All the submissions will go through rigorous blind review.Details on manuscript submission will be given online http://www.extreme-learning-machines.org/ELM2011 by April 15, 2011.

Important dates:

Paper submission deadline: June 1, 2011

Notification of acceptance: September 1, 2011

Registration deadline: October 15, 2011

 http://www.extreme-learning-machines.org/ELM2011