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New Trends of Learning in Computational Intelligence [Guest Editorial]

IEEE Computational Intelligence MagazinePublished 9 April 2015Open access
Guang-Bin Huang, Erik Cambria, Kar‐Ann Toh, Bernard Widrow, Zongben Xu
Citations49
SJR quartileQ1
SJR score1.85
SNIP3.05
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TL;DR

This special issue is dedicated to new trends of Learning in the field of computational intelligence, where emerging computational intelligence techniques such as extreme learning machines (ELM) and fast solutions shed some light upon how to effectively deal with computational bottlenecks.

Abstract

The articles in this special issue are dedicated to new trends of Learning in the field of computational intelligence. Over the past few decades, conventional computational intelligence techniques faced severe bottlenecks in terms of algorithmic learning. Particularly, in the 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 are to be employed before any meaningful observations can be obtained. 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.

Keywords

Computer Science