ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1711.03439
  4. Cited By
Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex
  Optimization

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization

9 November 2017
Ahmet Alacaoglu
Quoc Tran-Dinh
Olivier Fercoq
Volkan Cevher
ArXivPDFHTML

Papers citing "Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization"

4 / 4 papers shown
Title
Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems
Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems
Quoc Tran-Dinh
Yang Luo
128
8
0
28 Jan 2025
Smooth minimization of nonsmooth functions with parallel coordinate
  descent methods
Smooth minimization of nonsmooth functions with parallel coordinate descent methods
Olivier Fercoq
Peter Richtárik
33
33
0
23 Sep 2013
Parallel Coordinate Descent Methods for Big Data Optimization
Parallel Coordinate Descent Methods for Big Data Optimization
Peter Richtárik
Martin Takáč
94
487
0
04 Dec 2012
Stochastic Dual Coordinate Ascent Methods for Regularized Loss
  Minimization
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
Shai Shalev-Shwartz
Tong Zhang
121
1,031
0
10 Sep 2012
1