121 citations · 214 across the 22 of their papers we have counts for
4 papers · 1 filter
Power-law Dynamic arising from machine learning
Wei Chen, Weitao Du, Zhi-Ming Ma +1
We study a kind of new SDE that was arisen from the research on optimization in machine learning, we call it power-law dynamic because its stationary distribution cannot have sub-G…
Off-policy Learning for Multiple Loggers
Li He, Long Xia, Wei Zeng +3
It is well known that the historical logs are used for evaluating and learning policies in interactive systems, e.g. recommendation, search, and online advertising. Since direct on…
-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Qi Meng, Shuxin Zheng, Huishuai Zhang +3
It is well known that neural networks with rectified linear units (ReLU) activation functions are positively scale-invariant. Conventional algorithms like stochastic gradient desce…
Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling
Qi Meng, Wei Chen, Yue Wang +2
When using stochastic gradient descent to solve large-scale machine learning problems, a common practice of data processing is to shuffle the training data, partition the data acro…