399 citations · 3.4k across the 95 of their papers we have counts for
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The Teaching Dimension of Linear Learners
Ji Liu, Xiaojin Zhu
Teaching dimension is a learning theoretic quantity that specifies the minimum training set size to teach a target model to a learner. Previous studies on teaching dimension focuse…
Staleness-aware Async-SGD for Distributed Deep Learning
Wei Zhang, Suyog Gupta, Xiangru Lian +1
Deep neural networks have been shown to achieve state-of-the-art performance in several machine learning tasks. Stochastic Gradient Descent (SGD) is the preferred optimization algo…
Exclusive Sparsity Norm Minimization with Random Groups via Cone Projection
Yijun Huang, Ji Liu
Many practical applications such as gene expression analysis, multi-task learning, image recognition, signal processing, and medical data analysis pursue a sparse solution for the…
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Xiangru Lian, Yijun Huang, Yuncheng Li +1
Asynchronous parallel implementations of stochastic gradient (SG) have been broadly used in solving deep neural network and received many successes in practice recently. However, e…