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cs.LG2020
Regularization in network optimization via trimmed stochastic gradient descent with noisy label
Kensuke Nakamura, Bong-Soo Sohn, Kyoung-Jae Won +1
Regularization is essential for avoiding over-fitting to training data in network optimization, leading to better generalization of the trained networks. The label noise provides a…
cs.LG2020
Stochastic batch size for adaptive regularization in deep network optimization
Kensuke Nakamura, Stefano Soatto, Byung-Woo Hong
We propose a first-order stochastic optimization algorithm incorporating adaptive regularization applicable to machine learning problems in deep learning framework. The adaptive re…