Title

Efficient and Rapid Machine Learning Algorithms for Big Data and Dynamic Varying Systems

Abstract

With the exponential growth of data and complexity of systems, fast machine learning/artificial intelligence and computational intelligence techniques are highly required. Many conventional computational intelligence techniques face bottlenecks in learning (e.g., intensive human intervention and convergence time) [item 1) in the Appendix]. However, efficient learning algorithms alternatively offer significant benefits including fast learning speed, ease of implementation, and minimal human intervention. The need for efficient and fast implementation of machine learning techniques in big data and dynamic varying systems poses many research challenges. This special issue highlights some latest development in the related areas.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Artificial intelligence; Big data; Learning systems; Computational intelligence techniques; Convergence time; Exponential growth; Fast implementation; Human intervention; Latest development; Machine learning techniques; Research challenges; Learning algorithms

International Standard Serial Number (ISSN)

2168-2216

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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