DocumentCode :
20220
Title :
New Trends of Learning in Computational Intelligence [Guest Editorial]
Author :
Huang, Guang-Bin ; Cambria, Erik ; Toh, Kar-Ann ; Widrow, Bernard ; Xu, Zongben
Author_Institution :
Nanyang Technological University, Singapore
Volume :
10
Issue :
2
fYear :
2015
fDate :
May-15
Firstpage :
16
Lastpage :
17
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 :
Biological system modeling; Cognition; Computational intelligence; Computer science education; Human factors; Learning systems; Market research; Neural networks; Real-time systems; Special issues and sections;
fLanguage :
English
Journal_Title :
Computational Intelligence Magazine, IEEE
Publisher :
ieee
ISSN :
1556-603X
Type :
jour
DOI :
10.1109/MCI.2015.2405277
Filename :
7083692
Link To Document :
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