2 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.LG2019★ 2 cited
Learning Classifiers on Positive and Unlabeled Data with Policy Gradient
Tianyu Li, Chien-Chih Wang, Yukun Ma +4
Existing algorithms aiming to learn a binary classifier from positive (P) and unlabeled (U) data generally require estimating the class prior or label noises ahead of building a cl…
stat.ML2018★ 2 cited
Newton Methods for Convolutional Neural Networks
Chien-Chih Wang, Kent Loong Tan, Chih-Jen Lin
Deep learning involves a difficult non-convex optimization problem, which is often solved by stochastic gradient (SG) methods. While SG is usually effective, it may not be robust i…
stat.ML2018★ 1 cited
Distributed Newton Methods for Deep Neural Networks
Chien-Chih Wang, Kent Loong Tan, Chun-Ting Chen +5
Deep learning involves a difficult non-convex optimization problem with a large number of weights between any two adjacent layers of a deep structure. To handle large data sets or…