Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions

3 February 2019

Papers citing "Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions"

10 / 10 papers shown

Title
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities Aleksandr Beznosikov S. Samsonov Marina Sheshukova Alexander Gasnikov A. Naumov Eric Moulines 46 14 0 25 May 2023
Extragradient Method: $O(1/K)$ Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity Eduard A. Gorbunov Nicolas Loizou Gauthier Gidel 31 64 0 08 Oct 2021
Almost sure convergence rates for Stochastic Gradient Descent and Stochastic Heavy Ball Othmane Sebbouh Robert Mansel Gower Aaron Defazio 6 22 0 14 Jun 2020
Complexity Guarantees for Polyak Steps with Momentum Mathieu Barré Adrien B. Taylor Alexandre d’Aspremont 22 26 0 03 Feb 2020
From Nesterov's Estimate Sequence to Riemannian Acceleration Kwangjun Ahn S. Sra 22 74 0 24 Jan 2020
A frequency-domain analysis of inexact gradient methods Oran Gannot 24 25 0 31 Dec 2019
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems Ernest K. Ryu Kun Yuan W. Yin 20 36 0 26 May 2019
New Convergence Aspects of Stochastic Gradient Algorithms Lam M. Nguyen Phuong Ha Nguyen Peter Richtárik K. Scheinberg Martin Takáč Marten van Dijk 23 66 0 10 Nov 2018
Analysis of Biased Stochastic Gradient Descent Using Sequential Semidefinite Programs Bin Hu Peter M. Seiler Laurent Lessard 18 39 0 03 Nov 2017
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,201 0 16 Aug 2016