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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

Title
A Unified Analysis for the Subgradient Methods Minimizing Composite Nonconvex, Nonsmooth and Non-Lipschitz Functions Daoli Zhu Lei Zhao Shuzhong Zhang 121 3 0 30 Aug 2023
Non-ergodic linear convergence property of the delayed gradient descent under the strongly convexity and the Polyak-Łojasiewicz condition Hyunggwon Choi Woocheol Choi Jinmyoung Seok 85 0 0 23 Aug 2023
A Homogenization Approach for Gradient-Dominated Stochastic Optimization Jiyuan Tan Chenyu Xue Chuwen Zhang Qi Deng Dongdong Ge Yinyu Ye 87 2 0 21 Aug 2023
Variance reduction techniques for stochastic proximal point algorithms Cheik Traoré Vassilis Apidopoulos Saverio Salzo S. Villa 100 8 0 18 Aug 2023
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods A. Ma Yangchen Pan Amir-massoud Farahmand AAML 93 8 0 13 Aug 2023
Faster Stochastic Algorithms for Minimax Optimization under Polyak--Łojasiewicz Conditions Le‐Yu Chen Boyuan Yao Luo Luo 77 15 0 29 Jul 2023
Convergence of Adam for Non-convex Objectives: Relaxed Hyperparameters and Non-ergodic Case Meixuan He Yuqing Liang Jinlan Liu Dongpo Xu 114 9 0 20 Jul 2023
Zero-th Order Algorithm for Softmax Attention Optimization Yichuan Deng Zhihang Li Sridhar Mahadevan Zhao Song 83 14 0 17 Jul 2023
$Performance of $\ell_1$ Regularization for Sparse Convex Optimization$ Performance of $\ell_1$ Regularization for Sparse Convex Optimization Kyriakos Axiotis T. Yasuda 90 0 0 14 Jul 2023
Invex Programs: First Order Algorithms and Their Convergence Adarsh Barik S. Sra Jean Honorio 70 2 0 10 Jul 2023
Fairness-aware Federated Minimax Optimization with Convergence Guarantee Gerry Windiarto Mohamad Dunda Shenghui Song FedML 96 2 0 10 Jul 2023
Accelerated Optimization Landscape of Linear-Quadratic Regulator Le Feng Yuan‐Hua Ni 96 0 0 07 Jul 2023
Analyzing and Improving Greedy 2-Coordinate Updates for Equality-Constrained Optimization via Steepest Descent in the 1-Norm A. Ramesh Aaron Mishkin Mark Schmidt Yihan Zhou J. Lavington Jennifer She 78 2 0 03 Jul 2023
A First Order Meta Stackelberg Method for Robust Federated Learning Yunian Pan Tao Li Henger Li Tianyi Xu Zizhan Zheng Quanyan Zhu FedML 129 11 0 23 Jun 2023
Distributed Random Reshuffling Methods with Improved Convergence Kun-Yen Huang Linli Zhou Shi Pu 181 4 0 21 Jun 2023
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths Charles Guille-Escuret Hiroki Naganuma Kilian Fatras Ioannis Mitliagkas 102 4 0 20 Jun 2023
Convergence and concentration properties of constant step-size SGD through Markov chains Ibrahim Merad Stéphane Gaïffas 103 5 0 20 Jun 2023
Gradient is All You Need? Konstantin Riedl T. Klock Carina Geldhauser M. Fornasier 106 9 0 16 Jun 2023
Robustly Learning a Single Neuron via Sharpness Puqian Wang Nikos Zarifis Ilias Diakonikolas Jelena Diakonikolas 84 10 0 13 Jun 2023
Learning Unnormalized Statistical Models via Compositional Optimization Wei Jiang Jiayu Qin Lingyu Wu Changyou Chen Tianbao Yang Lijun Zhang 128 5 0 13 Jun 2023
Achieving Consensus over Compact Submanifolds Jiang Hu Jiaojiao Zhang Kangkang Deng 85 5 0 07 Jun 2023
Minimum intrinsic dimension scaling for entropic optimal transport Austin J. Stromme 96 11 0 06 Jun 2023
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems Chaoyue Liu Dmitriy Drusvyatskiy M. Belkin Damek Davis Yi-An Ma ODL 97 20 0 05 Jun 2023
Searching for Optimal Per-Coordinate Step-sizes with Multidimensional Backtracking Frederik Kunstner V. S. Portella Mark Schmidt Nick Harvey 125 10 0 05 Jun 2023
A Generalized Alternating Method for Bilevel Learning under the Polyak-Łojasiewicz Condition Quan-Wu Xiao Songtao Lu Tianyi Chen 146 3 0 04 Jun 2023
Gradient-free optimization of highly smooth functions: improved analysis and a new algorithm A. Akhavan Evgenii Chzhen Massimiliano Pontil Alexandre B. Tsybakov 102 12 0 03 Jun 2023
Solving Robust MDPs through No-Regret Dynamics E. Guha 106 0 0 30 May 2023
Knowledge Distillation Performs Partial Variance Reduction M. Safaryan Alexandra Peste Dan Alistarh 144 8 0 27 May 2023
Fine-Tuning Language Models with Just Forward Passes Sadhika Malladi Tianyu Gao Eshaan Nichani Alexandru Damian Jason D. Lee Danqi Chen Sanjeev Arora 223 241 0 27 May 2023
A Guide Through the Zoo of Biased SGD Yury Demidovich Grigory Malinovsky Igor Sokolov Peter Richtárik 124 32 0 25 May 2023
How to escape sharp minima with random perturbations Kwangjun Ahn Ali Jadbabaie S. Sra ODL 183 9 0 25 May 2023
On the Convergence of Black-Box Variational Inference Kyurae Kim Jisu Oh Kaiwen Wu Yi-An Ma Jacob R. Gardner BDL 120 17 0 24 May 2023
The Crucial Role of Normalization in Sharpness-Aware Minimization Yan Dai Kwangjun Ahn S. Sra 167 20 0 24 May 2023
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees Sharan Vaswani A. Kazemi Reza Babanezhad Nicolas Le Roux OffRL 137 4 0 24 May 2023
Improving Convergence and Generalization Using Parameter Symmetries Bo Zhao Robert Mansel Gower Robin Walters Rose Yu MoMe 165 16 0 22 May 2023
Classical-to-Quantum Transfer Learning Facilitates Machine Learning with Variational Quantum Circuit Jun Qi Chao-Han Huck Yang Pin-Yu Chen Min-hsiu Hsieh Hector Zenil Jesper Tegner 118 2 0 18 May 2023
Low-complexity subspace-descent over symmetric positive definite manifold Yogesh Darmwal K. Rajawat 162 3 0 03 May 2023
Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems? Yihan Zhang Wenhao Jiang Feng-Song Zheng C. C. Tan Xinghua Shi Hongchang Gao 67 1 0 24 Apr 2023
Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems Feihu Huang Songcan Chen 117 6 0 21 Apr 2023
Convergence of stochastic gradient descent under a local Lojasiewicz condition for deep neural networks Jing An Jianfeng Lu 95 5 0 18 Apr 2023
Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator Haobo Qi Feifei Wang Hansheng Wang 83 15 0 13 Apr 2023
Fast Convergence of Random Reshuffling under Over-Parameterization and the Polyak-Łojasiewicz Condition Chen Fan Christos Thrampoulidis Mark Schmidt 80 2 0 02 Apr 2023
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems Sihan Zeng Thinh T. Doan Justin Romberg OffRL 144 3 0 23 Mar 2023
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference Kyurae Kim Kaiwen Wu Jisu Oh Jacob R. Gardner BDL 143 8 0 18 Mar 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 103 6 0 08 Mar 2023
Amplitude-Varying Perturbation for Balancing Privacy and Utility in Federated Learning Xinnan Yuan W. Ni Ming Ding Kang Wei Jun Li H. Vincent Poor FedML 88 49 0 07 Mar 2023
On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level Feihu Huang 140 20 0 07 Mar 2023
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization Feihu Huang Chunyu Xuan Xinrui Wang Siqi Zhang Songcan Chen 228 8 0 07 Mar 2023
Fast and Interpretable Dynamics for Fisher Markets via Block-Coordinate Updates Tianlong Nan Yuan Gao Christian Kroer 139 3 0 01 Mar 2023
From Optimization to Sampling Through Gradient Flows Nicolas García Trillos B. Hosseini D. Sanz-Alonso 67 12 0 22 Feb 2023