Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization

17 May 2018

Papers citing "Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization"

10 / 60 papers shown

Title
Diffusion Adaptation Strategies for Distributed Optimization and Learning over Networks Jianshu Chen Ali H. Sayed 78 652 0 31 Oct 2011
Optimization with Sparsity-Inducing Penalties Francis R. Bach Rodolphe Jenatton Julien Mairal G. Obozinski 155 1,058 0 03 Aug 2011
Convergence of a Multi-Agent Projected Stochastic Gradient Algorithm for Non-Convex Optimization Pascal Bianchi J. Jakubowicz 88 254 0 13 Jul 2011
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright 130 2,272 0 28 Jun 2011
Parallel Coordinate Descent for L1-Regularized Loss Minimization Joseph K. Bradley Aapo Kyrola Danny Bickson Carlos Guestrin 66 309 0 26 May 2011
Algorithms for nonnegative matrix factorization with the beta-divergence Cédric Févotte Jérôme Idier 81 802 0 08 Oct 2010
MM Algorithms for Geometric and Signomial Programming K. Lange Hua Zhou 103 46 0 14 Jul 2010
Structured Sparse Principal Component Analysis Rodolphe Jenatton G. Obozinski Francis R. Bach 125 353 0 08 Sep 2009
Rank-Sparsity Incoherence for Matrix Decomposition V. Chandrasekaran Sujay Sanghavi P. Parrilo A. Willsky CML 166 1,111 0 11 Jun 2009
Enhancing Sparsity by Reweighted L1 Minimization Emmanuel J. Candes M. Wakin Stephen P. Boyd 157 5,027 0 10 Nov 2007