17 citations · 54 across the 14 of their papers we have counts for
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stat.ML2016
Lock-Free Optimization for Non-Convex Problems
Shen-Yi Zhao, Gong-Duo Zhang, Wu-Jun Li
Stochastic gradient descent~(SGD) and its variants have attracted much attention in machine learning due to their efficiency and effectiveness for optimization. To handle large-sca…
stat.ML2016★ 5 cited
SCOPE: Scalable Composite Optimization for Learning on Spark
Shen-Yi Zhao, Ru Xiang, Ying-Hao Shi +2
Many machine learning models, such as logistic regression~(LR) and support vector machine~(SVM), can be formulated as composite optimization problems. Recently, many distributed st…