Title
Deep Learning Optimization Tasks and Metaheuristic Methods.
Abstract
In this paper we identify and formulate two optimization tasks solved in connection with training DL models and constructing adversarial examples. This guides our review of optimization methods commonly used within the DL community. Simultaneously, we present findings from the literature concerning metaheuristics and black-box optimization. We focus on well-known optimizers suitable for solving R-N tasks, which achieve good results on benchmarks and in competitions. Finally, we look into the research connected with utilizing metaheuristic optimization methods in combination with deep learning models.
Year
DOI
Venue
2019
10.3233/FI-2019-1828
FUNDAMENTA INFORMATICAE
Keywords
Field
DocType
Deep learning,metaheuristics,optimization
Discrete mathematics,Artificial intelligence,Deep learning,Mathematics,Metaheuristic
Journal
Volume
Issue
ISSN
168
2-4
0169-2968
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Rafal Biedrzycki172.82
Pawel Zawistowski2151.66
Bartlomiej Twardowski3251.83