ELM 2014 - The 5th International Conference on Extreme Learning Machines (ELM2014)

The 5th International Conference on Extreme Learning Machines (ELM2014)
Marina Bay Sands, Singapore, December 8 - 10, 2014
(Paper submission system is now open!)
Organizer: Nanyang Technological University, Singapore
Co-Organizers: National University of Singapore; Tsinghua University, China
Extreme Learning Machines (ELM) aim to break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of machine learning techniques in which hidden neurons need not be tuned. ELM learning theories show that hidden neurons (with almost any nonlinear activation functions) can be randomly generated independent of training data and application environments, which has recently been confirmed with concrete biological evidences. ELM theories and algorithms argue that “random hidden neurons” capture the essence of some brain learning mechanism as well as the intuitive sense that the efficiency of brain learning need not rely on computing power of neurons. This may somehow hint at possible reasons why brain is more intelligent and effective than computers. ELM offers significant advantages such as fast learning speed, ease of implementation, and minimal human intervention. ELM has good potential as a viable alternative technique for large-scale computing and artificial intelligence.
The main theme of ELM2014 is: Big Data Analytics and Machine Learning
Organized by Nanyang Technological University, and co-organized by Tsinghua University and National University of Singapore, ELM2014 will be held in the beautiful island-country of Singapore. This conference 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 and brain learning.
Accepted papers presented in this conference will be recommended to reputable ISI indexed international journals (Neurocomputing, Cognitive Computation, Mathematical Problems in Engineering, etc) or special edited book volumes to be published by Springer-Verlag.
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 and stability analysis
Algorithms
Real-time learning, reasoning and cognition
Sequential/incremental learning and kernel learning
Clustering and feature extraction/selection
Random projection, dimensionality reduction, and matrix factorization
Closed form and non-closed form solutions
Multi hidden layers solutions and random networks
Parallel and distributed computing / cloud computing
Applications
Time series prediction
Pattern recognition
Web applications
Biometrics and bioinformatics
Power systems and control engineering
Security and compression
Human computer interface and brain computer interface
Cognitive science/computation
Sentic computing / natural language processing
Data analytics, super / ultra large-scale data processing
Paper submission:
Potential authors may submit their manuscripts for publication consideration either in special issues of journals or edited book volumes. Only full-length manuscripts with at least submission entry quality of good journals will be considered for presentation at this conference. All the submissions will go through rigorous peer review. Details on manuscript submission can be found from http://elm2014.extreme-learning-machines.org
Important dates:
Paper submission deadline: June 1, 2014
Notification of acceptance: July 15, 2014
Registration deadline: September 1, 2014