Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection

1 June 2015

Papers citing "Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection"

11 / 11 papers shown

Title
Joker: Joint Optimization Framework for Lightweight Kernel Machines Junhong Zhang Zhihui Lai 30 0 0 23 May 2025
MoFO: Momentum-Filtered Optimizer for Mitigating Forgetting in LLM Fine-Tuning Yupeng Chen Senmiao Wang Zhihang Lin Zhihang Lin Yushun Zhang Tian Ding Ruoyu Sun Ruoyu Sun CLL 125 3 0 30 Jul 2024
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation Sobihan Surendran Antoine Godichon-Baggioni Adeline Fermanian Sylvain Le Corff 77 1 0 05 Feb 2024
Coordinate Friendly Structures, Algorithms and Applications Zhimin Peng Tianyu Wu Yangyang Xu Ming Yan W. Yin 46 74 0 05 Jan 2016
Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS) Anshumali Shrivastava Ping Li 100 470 0 22 May 2014
Accelerated, Parallel and Proximal Coordinate Descent Olivier Fercoq Peter Richtárik 64 372 0 20 Dec 2013
Parallel Coordinate Descent Methods for Big Data Optimization Peter Richtárik Martin Takáč 88 487 0 04 Dec 2012
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 115 1,031 0 10 Sep 2012
Greedy Block Coordinate Descent for Large Scale Gaussian Process Regression Liefeng Bo C. Sminchisescu 46 25 0 13 Jun 2012
Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function Peter Richtárik Martin Takáč 83 769 0 14 Jul 2011
Hybrid Deterministic-Stochastic Methods for Data Fitting M. Friedlander Mark Schmidt 129 387 0 13 Apr 2011