Call for Papers

IEEE Computational Intelligence Magazine

Special Issue on “New Trends of Learning in Computational Intelligence”

A special issue of the IEEE Computational Intelligence Magazine (IEEE CIM) will be dedicated to New Trends of Learning in Computational Intelligence. Prospective authors are invited to submit their original unpublished research and application contributions. Comprehensive tutorial and survey papers can also be considered for this special issue.

Over the past few decades, conventional computational intelligence techniques faced severe bottlenecks in terms of algorithmic learning. Particularly, in areas of big data computation, brain science, cognition and reasoning, it is almost inevitable that intensive human intervention and time consuming trial and error efforts need to be employed before any meaningful observations can be obtained. The recent development of emerging computational intelligence techniques such as extreme learning machines (ELM) and fast solutions shed some light upon how to effectively deal with these computational bottlenecks.

Based on the observations that increasing correlation can be found among apparently different theories from different fields, as well as the increasing evidence of convergence between computational intelligence techniques and biological learning mechanisms, this special issue seeks to promote novel research investigations in computational intelligence bridging among related areas.

Topics of interest for this special issue include but are not limited to:

• Theoretical foundations and algorithms:

–          Extreme learning machines (ELM), No-Prop algorithms and random kitchen sinks

–          Real-time learning, reasoning and cognition

–          Sequential / incremental learning

–          Clustering and feature extraction / selection

–          Closed form and non-closed form solutions

–          Multiple hidden layers solutions and random networks

–          Parallel and distributed computing / cloud computing

–          Fast implementation of deep learning

• Applications

–          Biologically-inspired natural language processing

–          Big data analytics

–          Cognitive science / computation

–          Autonomous systems

Deadlines

15th August, 2014: Submission of Manuscripts

15th October, 2014: Notification of Review Results

15th November, 2014: Submission of Revised Manuscripts

15th December, 2014: Submission of Final Manuscripts

Publication: May 2015 Issue

Paper Submission

The maximum length for the manuscript is typically 25 pages in single column format with double-spacing, including figures and references. Authors should specify in the first page of their manuscripts the corresponding author’s contact and up to 5 keywords. Submission should be made via https://www.easychair.org/conferences/?conf=ieeecimmay2015.

Guest Editors

Guang-Bin Huang, Nanyang Technological University, egbhuang@ntu.edu.sg

Erik Cambria, MIT Media Laboratory, USA, cambria@media.mit.edu

Kar-Ann Toh, Yonsei University, South Korea, katoh@yonsei.ac.kr

Bernard Widrow, Stanford University, USA, widrow@stanford.edu

Zongben Xu, Xi’an Jiaotong University, China, zbxu@mail.xjtu.edu.cn