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Deep Neural Network Hyperparameter Optimization with Orthogonal Array Tuning
[article]
2020
arXiv
pre-print
Deep learning algorithms have achieved excellent performance lately in a wide range of fields (e.g., computer version). However, a severe challenge faced by deep learning is the high dependency on hyper-parameters. The algorithm results may fluctuate dramatically under the different configuration of hyper-parameters. Addressing the above issue, this paper presents an efficient Orthogonal Array Tuning Method (OATM) for deep learning hyper-parameter tuning. We describe the OATM approach in five
arXiv:1907.13359v2
fatcat:axzzzmzchvhfjiba6te2i5hzgm