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

16 August 2016

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

50 / 602 papers shown

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Communication-Censored Distributed Stochastic Gradient Descent Weiyu Li Tianyi Chen Liping Li Zhaoxian Wu Qing Ling 64 19 0 09 Sep 2019
Stochastic AUC Maximization with Deep Neural Networks Mingrui Liu Zhuoning Yuan Yiming Ying Tianbao Yang 119 109 0 28 Aug 2019
Proximal gradient flow and Douglas-Rachford splitting dynamics: global exponential stability via integral quadratic constraints Sepideh Hassan-Moghaddam Mihailo R. Jovanović 42 0 0 23 Aug 2019
Towards Better Generalization: BP-SVRG in Training Deep Neural Networks Hao Jin Dachao Lin Zhihua Zhang ODL 67 2 0 18 Aug 2019
Path Length Bounds for Gradient Descent and Flow Chirag Gupta Sivaraman Balakrishnan Aaditya Ramdas 152 15 0 02 Aug 2019
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift Alekh Agarwal Sham Kakade Jason D. Lee G. Mahajan 239 323 0 01 Aug 2019
Sparse Optimization on Measures with Over-parameterized Gradient Descent Lénaïc Chizat 120 98 0 24 Jul 2019
signADAM: Learning Confidences for Deep Neural Networks Dong Wang Yicheng Liu Wenwo Tang Fanhua Shang Hongying Liu Qigong Sun Licheng Jiao ODL FedML 39 1 0 21 Jul 2019
A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization Quoc Tran-Dinh Nhan H. Pham T. Dzung Lam M. Nguyen 93 53 0 08 Jul 2019
The Role of Memory in Stochastic Optimization Antonio Orvieto Jonas Köhler Aurelien Lucchi 104 32 0 02 Jul 2019
Near-Optimal Methods for Minimizing Star-Convex Functions and Beyond Oliver Hinder Aaron Sidford N. Sohoni 139 76 0 27 Jun 2019
A Stochastic Composite Gradient Method with Incremental Variance Reduction Junyu Zhang Lin Xiao 88 69 0 24 Jun 2019
Tensor Canonical Correlation Analysis with Convergence and Statistical Guarantees You-Lin Chen Mladen Kolar R. Tsay 141 0 0 12 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 137 40 0 09 Jun 2019
Last-iterate convergence rates for min-max optimization Jacob D. Abernethy Kevin A. Lai Andre Wibisono 156 74 0 05 Jun 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 200 203 0 05 Jun 2019
Sparse optimal control of networks with multiplicative noise via policy gradient Benjamin J. Gravell Yi Guo Tyler H. Summers 33 3 0 28 May 2019
Learning robust control for LQR systems with multiplicative noise via policy gradient Benjamin J. Gravell Peyman Mohajerin Esfahani Tyler H. Summers 123 26 0 28 May 2019
Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization Yifan Hu Xin Chen Niao He 114 37 0 28 May 2019
One Method to Rule Them All: Variance Reduction for Data, Parameters and Many New Methods Filip Hanzely Peter Richtárik 140 27 0 27 May 2019
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates Sharan Vaswani Aaron Mishkin I. Laradji Mark Schmidt Gauthier Gidel Simon Lacoste-Julien ODL 196 213 0 24 May 2019
Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function A. Raghunathan A. Cherian Devesh K. Jha 66 22 0 15 May 2019
On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization Hao Yu Rong Jin 104 51 0 10 May 2019
On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms Nhat Ho Tianyi Lin Michael I. Jordan 154 3 0 16 Apr 2019
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent Karthik A. Sankararaman Soham De Zheng Xu Wenjie Huang Tom Goldstein ODL 196 108 0 15 Apr 2019
Controlling Neural Networks via Energy Dissipation Michael Möller Thomas Möllenhoff Zorah Lähner 119 17 0 05 Apr 2019
Convergence rates for the stochastic gradient descent method for non-convex objective functions Benjamin J. Fehrman Benjamin Gess Arnulf Jentzen 121 103 0 02 Apr 2019
Provable Guarantees for Gradient-Based Meta-Learning M. Khodak Maria-Florina Balcan Ameet Talwalkar FedML 177 152 0 27 Feb 2019
A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing Sirisha Rambhatla Xingguo Li Jineng Ren Jarvis Haupt 72 6 0 26 Feb 2019
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods Maher Nouiehed Maziar Sanjabi Tianjian Huang Jason D. Lee Meisam Razaviyayn 154 347 0 21 Feb 2019
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization Nhan H. Pham Lam M. Nguyen Dzung Phan Quoc Tran-Dinh 91 141 0 15 Feb 2019
An adaptive stochastic optimization algorithm for resource allocation Xavier Fontaine Shie Mannor Vianney Perchet 70 13 0 12 Feb 2019
Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions Adrien B. Taylor Francis R. Bach 120 67 0 03 Feb 2019
Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions Yunwen Lei Ting Hu Guiying Li Shengcai Liu MLT 144 120 0 03 Feb 2019
ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding Hongyi Wang Zachary B. Charles Dimitris Papailiopoulos 66 55 0 28 Jan 2019
SGD: General Analysis and Improved Rates Robert Mansel Gower Nicolas Loizou Xun Qian Alibek Sailanbayev Egor Shulgin Peter Richtárik 149 400 0 27 Jan 2019
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization Zhenxun Zhuang Ashok Cutkosky Francesco Orabona 162 5 0 25 Jan 2019
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path? Samet Oymak Mahdi Soltanolkotabi ODL 152 180 0 25 Dec 2018
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems Dhruv Malik A. Pananjady Kush S. Bhatia K. Khamaru Peter L. Bartlett Martin J. Wainwright 130 207 0 20 Dec 2018
Stagewise Training Accelerates Convergence of Testing Error Over SGD Zhuoning Yuan Yan Yan Rong Jin Tianbao Yang 137 11 0 10 Dec 2018
Solving Non-Convex Non-Concave Min-Max Games Under Polyak-Łojasiewicz Condition Maziar Sanjabi Meisam Razaviyayn Jason D. Lee 85 35 0 07 Dec 2018
Inexact SARAH Algorithm for Stochastic Optimization Lam M. Nguyen K. Scheinberg Martin Takáč 104 52 0 25 Nov 2018
On exponential convergence of SGD in non-convex over-parametrized learning Xinhai Liu M. Belkin Yu-Shen Liu 130 105 0 06 Nov 2018
Uniform Convergence of Gradients for Non-Convex Learning and Optimization Dylan J. Foster Ayush Sekhari Karthik Sridharan 123 72 0 25 Oct 2018
SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms Zhe Wang Kaiyi Ji Yi Zhou Yingbin Liang Vahid Tarokh ODL 107 82 0 25 Oct 2018
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani Francis R. Bach Mark Schmidt 185 305 0 16 Oct 2018
Efficient Greedy Coordinate Descent for Composite Problems Sai Praneeth Karimireddy Anastasia Koloskova Sebastian U. Stich Martin Jaggi 77 30 0 16 Oct 2018
Continuous-time Models for Stochastic Optimization Algorithms Antonio Orvieto Aurelien Lucchi 139 32 0 05 Oct 2018
Newton-MR: Inexact Newton Method With Minimum Residual Sub-problem Solver Fred Roosta Yang Liu Peng Xu Michael W. Mahoney 139 16 0 30 Sep 2018
Exponential Convergence Time of Gradient Descent for One-Dimensional Deep Linear Neural Networks Ohad Shamir 129 47 0 23 Sep 2018