794 citations · 2.7k across the 93 of their papers we have counts for
Showing 2015 · stat.MLShow all
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stat.ML2015★ 1 cited
Stochastic Parallel Block Coordinate Descent for Large-scale Saddle Point Problems
Zhanxing Zhu, Amos J. Storkey
We consider convex-concave saddle point problems with a separable structure and non-strongly convex functions. We propose an efficient stochastic block coordinate descent method us…
stat.ML2015★ 13 cited
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling
Xiaocheng Shang, Zhanxing Zhu, Benedict Leimkuhler +1
Monte Carlo sampling for Bayesian posterior inference is a common approach used in machine learning. The Markov Chain Monte Carlo procedures that are used are often discrete-time a…
stat.ML2015★ 11 cited
Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems
Zhanxing Zhu, Amos J. Storkey
We consider a generic convex-concave saddle point problem with separable structure, a form that covers a wide-ranged machine learning applications. Under this problem structure, we…