Accelerated Linear Convergence of Stochastic Momentum Methods in
Wasserstein Distances

v1v2 (latest)

Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances

22 January 2019

Mert Gurbuzbalaban

ArXiv (abs)PDF HTML

Papers citing "Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances"

19 / 19 papers shown

Title
A Universally Optimal Multistage Accelerated Stochastic Gradient Method N. Aybat Alireza Fallah Mert Gurbuzbalaban Asuman Ozdaglar ODL 68 56 0 23 Jan 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks Umut Simsekli Levent Sagun Mert Gurbuzbalaban 100 252 0 18 Jan 2019
Breaking Reversibility Accelerates Langevin Dynamics for Global Non-Convex Optimization Xuefeng Gao Mert Gurbuzbalaban Lingjiong Zhu 56 31 0 19 Dec 2018
Accelerated Gossip via Stochastic Heavy Ball Method Nicolas Loizou Peter Richtárik 44 27 0 23 Sep 2018
Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions N. Aybat Alireza Fallah Mert Gurbuzbalaban Asuman Ozdaglar 48 59 0 27 May 2018
Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods Nicolas Loizou Peter Richtárik 73 201 0 27 Dec 2017
Linearly convergent stochastic heavy ball method for minimizing generalization error Nicolas Loizou Peter Richtárik 111 45 0 30 Oct 2017
Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains Aymeric Dieuleveut Alain Durmus Francis R. Bach 62 156 0 20 Jul 2017
Accelerating Stochastic Gradient Descent For Least Squares Regression Prateek Jain Sham Kakade Rahul Kidambi Praneeth Netrapalli Aaron Sidford 68 84 0 26 Apr 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 73 521 0 13 Feb 2017
Stochastic Heavy Ball S. Gadat Fabien Panloup Sofiane Saadane 102 104 0 14 Sep 2016
Local Minimax Complexity of Stochastic Convex Optimization Yuancheng Zhu S. Chatterjee John C. Duchi John D. Lafferty 26 31 0 24 May 2016
Unified Convergence Analysis of Stochastic Momentum Methods for Convex and Non-convex Optimization Tianbao Yang Qihang Lin Zhe Li 61 122 0 12 Apr 2016
Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression Aymeric Dieuleveut Nicolas Flammarion Francis R. Bach ODL 54 227 0 17 Feb 2016
Adding Gradient Noise Improves Learning for Very Deep Networks Arvind Neelakantan Luke Vilnis Quoc V. Le Ilya Sutskever Lukasz Kaiser Karol Kurach James Martens AI4CE ODL 83 545 0 21 Nov 2015
From Averaging to Acceleration, There is Only a Step-size Nicolas Flammarion Francis R. Bach 94 139 0 07 Apr 2015
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition Rong Ge Furong Huang Chi Jin Yang Yuan 140 1,059 0 06 Mar 2015
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights Weijie Su Stephen P. Boyd Emmanuel J. Candes 162 1,173 0 04 Mar 2015
Convex Optimization: Algorithms and Complexity Sébastien Bubeck 82 112 0 20 May 2014