Connectionists: [SenticNet] CFP: IEEE CIM Special Issue on New Trends of Learning in Computational Intelligence

[SenticNet]

Apologies for cross-posting,

A special issue of the IEEE Computational Intelligence Magazine 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authors are invited to submit their original unpublished research and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.

RATIONALE
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
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
     • Situation / Intention Awareness

TIMEFRAME
• 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
• May, 2015: Publication

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 email to any of the
guest editors listed below.

GUEST EDITORS
• Guang-Bin Huang, Nanyang Technological University (Singapore)
• Erik Cambria, Nanyang Technological University (Singapore)
• Kar-Ann Toh, Yonsei University (South Korea)
• Bernard Widrow, Stanford University (USA)
• Zongben Xu, Xi'an Jiaotong University (China)