Coordinate Descent with Arbitrary Sampling II: Expected Separable Overapproximation

27 December 2014

Papers citing "Coordinate Descent with Arbitrary Sampling II: Expected Separable Overapproximation"

9 / 9 papers shown

Title
Laplacian-based Semi-Supervised Learning in Multilayer Hypergraphs by Coordinate Descent Sara Venturini Andrea Cristofari Francesco Rinaldi Francesco Tudisco 39 2 0 28 Jan 2023
GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity A. Maranjyan M. Safaryan Peter Richtárik 34 13 0 28 Oct 2022
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 32 0 0 26 Aug 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton Michal Derezinski Feynman T. Liang Zhenyu A. Liao Michael W. Mahoney 34 23 0 18 Jun 2020
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling Mojmír Mutný Michal Derezinski Andreas Krause 35 20 0 25 Oct 2019
99% of Distributed Optimization is a Waste of Time: The Issue and How to Fix it Konstantin Mishchenko Filip Hanzely Peter Richtárik 16 13 0 27 Jan 2019
SEGA: Variance Reduction via Gradient Sketching Filip Hanzely Konstantin Mishchenko Peter Richtárik 25 71 0 09 Sep 2018
Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods Nicolas Loizou Peter Richtárik 19 199 0 27 Dec 2017
Stochastic Dual Coordinate Ascent with Adaptive Probabilities Dominik Csiba Zheng Qu Peter Richtárik ODL 61 97 0 27 Feb 2015