Proximal SCOPE for Distributed Sparse Learning: Better Data Partition Implies Faster Convergence Rate

15 March 2018

Papers citing "Proximal SCOPE for Distributed Sparse Learning: Better Data Partition Implies Faster Convergence Rate"

8 / 8 papers shown

Title
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 111 196 0 23 Jun 2015
A distributed block coordinate descent method for training $l_1$ regularized linear classifiers D. Mahajan S. Keerthi S. Sundararajan 168 35 0 18 May 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 150 738 0 19 Mar 2014
A Stochastic Quasi-Newton Method for Large-Scale Optimization R. Byrd Samantha Hansen J. Nocedal Y. Singer ODL 105 471 0 27 Jan 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 316 1,245 0 10 Sep 2013
Parallel Coordinate Descent Methods for Big Data Optimization Peter Richtárik Martin Takáč 125 487 0 04 Dec 2012
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 178 1,033 0 10 Sep 2012
Parallel Coordinate Descent for L1-Regularized Loss Minimization Joseph K. Bradley Aapo Kyrola Danny Bickson Carlos Guestrin 95 309 0 26 May 2011