Automated design of machine learning and search algorithms

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Authors

Pillay, Nelishia
Qu, Rong
Srinivasan, Dipti
Hammer, Barbara
Sorensen, Kenneth

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers

Abstract

The three articles in this special section focus on the development of automated design of machine learning and search algorithms. There is a demand, especially from industry and business, to automate the design of machine learning and search algorithms, thereby removing the heavy reliance on human experts. Machine learning and search techniques play an important role in solving real-world complex optimization problems in areas such as transportation, data mining, computer vision, computer security and software development, amongst others. Given the growing complexity of optimization problems, the design of effective algorithms to solve these problems has become more challenging and time consuming. The design process is itself an optimization problem. Hence, there is a demand, especially from industry and business, to automate the design process, thereby to remove the heavy reliance on human experts and to reduce the man hours involved in designing machine learning and search algorithms.

Description

Keywords

Expert systems, Decision making, Heuristic algorithms, Software algorithms, Algorithm design and analysis, Machine learning, Special issues and sections

Sustainable Development Goals

Citation

Pillay, N., Qu, R., Srinivasan, D. et al. 2018, 'Automated design of machine learning and search algorithms', IEEE Computational Intelligence Magazine, vol. 13, no. 2, pp. 16-17.