15 citations · 94 across the 22 of their papers we have counts for
Showing 2016Show all
3 papers · 1 filter
stat.ML2016★ 1 cited
Accelerated Variance Reduced Block Coordinate Descent
Zebang Shen, Hui Qian, Chao Zhang +1
Algorithms with fast convergence, small number of data access, and low per-iteration complexity are particularly favorable in the big data era, due to the demand for obtaining \emp…
math.NA2016★ 2 cited
Accelerated Stochastic ADMM with Variance Reduction
Chao Zhang, Zebang Shen, Hui Qian +3
Alternating Direction Method of Multipliers (ADMM) is a popular method for solving large-scale Machine Learning problems. Stochastic ADMM was proposed to reduce the per iteration c…
stat.ML2016★ 2 cited
Riemannian Tensor Completion with Side Information
Tengfei Zhou, Hui Qian, Zebang Shen +1
By restricting the iterate on a nonlinear manifold, the recently proposed Riemannian optimization methods prove to be both efficient and effective in low rank tensor completion pro…