Papers citing 'Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition'

Title
SEGA: Variance Reduction via Gradient Sketching Filip Hanzely Konstantin Mishchenko Peter Richtárik 124 73 0 09 Sep 2018
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property Yi Zhou Zhe Wang Yingbin Liang 96 23 0 22 Aug 2018
Discrete linear-complexity reinforcement learning in continuous action spaces for Q-learning algorithms P. Tavallali G. Doran L. Mandrake 41 0 0 16 Jul 2018
Accelerating likelihood optimization for ICA on real signals Pierre Ablin J. Cardoso Alexandre Gramfort 43 2 0 25 Jun 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 119 149 0 20 Jun 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification Hongyi Wang Scott Sievert Zachary B. Charles Shengchao Liu S. Wright Dimitris Papailiopoulos 124 359 0 11 Jun 2018
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning Tianyi Chen G. Giannakis Tao Sun W. Yin 101 304 0 25 May 2018
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes Xiaoyun Li Francesco Orabona 176 309 0 21 May 2018
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions Mingrui Liu Xiaoxuan Zhang Lijun Zhang Rong Jin Tianbao Yang 99 26 0 11 May 2018
Frank-Wolfe Splitting via Augmented Lagrangian Method Gauthier Gidel Fabian Pedregosa Simon Lacoste-Julien 80 30 0 09 Apr 2018
Revisiting Decomposable Submodular Function Minimization with Incidence Relations Pan Li O. Milenkovic 158 19 0 10 Mar 2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem Andre Wibisono 157 188 0 22 Feb 2018
Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization Yi Zhou Yingbin Liang Huishuai Zhang MLT 113 26 0 19 Feb 2018
Robust Estimation via Robust Gradient Estimation Adarsh Prasad A. Suggala Sivaraman Balakrishnan Pradeep Ravikumar 151 221 0 19 Feb 2018
Differentially Private Empirical Risk Minimization Revisited: Faster and More General Di Wang Minwei Ye Jinhui Xu 158 275 0 14 Feb 2018
Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity Dan Garber 102 6 0 13 Feb 2018
Fast Global Convergence via Landscape of Empirical Loss Chao Qu Yan Li Huan Xu 44 0 0 13 Feb 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization Zhize Li Jian Li 140 119 0 13 Feb 2018
signSGD: Compressed Optimisation for Non-Convex Problems Jeremy Bernstein Yu Wang Kamyar Azizzadenesheli Anima Anandkumar FedML ODL 262 1,098 0 13 Feb 2018
On the Proximal Gradient Algorithm with Alternated Inertia F. Iutzeler J. Malick 49 33 0 17 Jan 2018
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator Maryam Fazel Rong Ge Sham Kakade M. Mesbahi 169 627 0 15 Jan 2018
A Stochastic Trust Region Algorithm Based on Careful Step Normalization Frank E. Curtis K. Scheinberg R. Shi 110 46 0 29 Dec 2017
Run-and-Inspect Method for Nonconvex Optimization and Global Optimality Bounds for R-Local Minimizers Yifan Chen Yuejiao Sun W. Yin 59 5 0 22 Nov 2017
Riemannian Optimization via Frank-Wolfe Methods Melanie Weber S. Sra 103 35 0 30 Oct 2017
Stability and Generalization of Learning Algorithms that Converge to Global Optima Zachary B. Charles Dimitris Papailiopoulos MLT 122 169 0 23 Oct 2017
Characterization of Gradient Dominance and Regularity Conditions for Neural Networks Yi Zhou Yingbin Liang 138 33 0 18 Oct 2017
A Modular Analysis of Adaptive (Non-)Convex Optimization: Optimism, Composite Objectives, and Variational Bounds Pooria Joulani András Gyorgy Csaba Szepesvári 98 44 0 08 Sep 2017
Nonconvex Sparse Logistic Regression with Weakly Convex Regularization Xinyue Shen Yuantao Gu 140 31 0 07 Aug 2017
A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints Bin Hu Peter M. Seiler Anders Rantzer 130 36 0 25 Jun 2017
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning Dong Yin A. Pananjady Max Lam Dimitris Papailiopoulos Kannan Ramchandran Peter L. Bartlett 107 11 0 18 Jun 2017
YellowFin and the Art of Momentum Tuning Jian Zhang Ioannis Mitliagkas ODL 136 109 0 12 Jun 2017
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients Lukas Balles Philipp Hennig 178 180 0 22 May 2017
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization Qunwei Li Yi Zhou Yingbin Liang P. Varshney 137 99 0 14 May 2017
Linear Convergence of Accelerated Stochastic Gradient Descent for Nonconvex Nonsmooth Optimization Feihu Huang Songcan Chen 71 2 0 26 Apr 2017
Faster Subgradient Methods for Functions with Hölderian Growth Patrick R. Johnstone P. Moulin 94 36 0 01 Apr 2017
Convergence of the Forward-Backward Algorithm: Beyond the Worst Case with the Help of Geometry Guillaume Garrigos Lorenzo Rosasco S. Villa 137 43 0 28 Mar 2017
Online Learning Rate Adaptation with Hypergradient Descent A. G. Baydin R. Cornish David Martínez-Rubio Mark Schmidt Frank Wood ODL 178 255 0 14 Mar 2017
Learn-and-Adapt Stochastic Dual Gradients for Network Resource Allocation Tianyi Chen Qing Ling G. Giannakis 106 22 0 05 Mar 2017
How to Escape Saddle Points Efficiently Chi Jin Rong Ge Praneeth Netrapalli Sham Kakade Michael I. Jordan ODL 314 853 0 02 Mar 2017
SAGA and Restricted Strong Convexity Chao Qu Yan Li Huan Xu 85 5 0 19 Feb 2017
Linear convergence of SDCA in statistical estimation Chao Qu Huan Xu 90 8 0 26 Jan 2017
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization Xingguo Li Junwei Lu R. Arora Jarvis Haupt Han Liu Zhaoran Wang T. Zhao 117 53 0 29 Dec 2016
Projected Semi-Stochastic Gradient Descent Method with Mini-Batch Scheme under Weak Strong Convexity Assumption Jie Liu Martin Takáč ODL 163 4 0 16 Dec 2016
The Physical Systems Behind Optimization Algorithms Lin F. Yang R. Arora Vladimir Braverman T. Zhao AI4CE 113 19 0 08 Dec 2016
Adaptive Accelerated Gradient Converging Methods under Holderian Error Bound Condition Mingrui Liu Tianbao Yang 114 15 0 23 Nov 2016
Identity Matters in Deep Learning Moritz Hardt Tengyu Ma OOD 227 402 0 14 Nov 2016
CoCoA: A General Framework for Communication-Efficient Distributed Optimization Virginia Smith Simone Forte Chenxin Ma Martin Takáč Michael I. Jordan Martin Jaggi 142 275 0 07 Nov 2016
Linear Convergence of SVRG in Statistical Estimation Chao Qu Yan Li Huan Xu 110 11 0 07 Nov 2016
Big Batch SGD: Automated Inference using Adaptive Batch Sizes Soham De A. Yadav David Jacobs Tom Goldstein ODL 241 62 0 18 Oct 2016
Accelerating Stochastic Composition Optimization Mengdi Wang Ji Liu Ethan X. Fang 104 149 0 25 Jul 2016