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 / 167 papers shown

Title
Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles Amir Ali Farzin Yuen-Man Pun Iman Shames 31 0 0 04 May 2025
Towards Trustworthy Federated Learning with Untrusted Participants Youssef Allouah R. Guerraoui John Stephan FedML 46 0 0 03 May 2025
Stochastic Subspace Descent Accelerated via Bi-fidelity Line Search Nuojin Cheng Alireza Doostan Stephen Becker 39 0 0 30 Apr 2025
AlphaGrad: Non-Linear Gradient Normalization Optimizer Soham Sane ODL 48 0 0 22 Apr 2025
Investigating Large Language Models in Diagnosing Students' Cognitive Skills in Math Problem-solving Hyoungwook Jin Yoonsu Kim Dongyun Jung Seungju Kim Kiyoon Choi J. Son Juho Kim LRM 58 0 0 01 Apr 2025
Gradient-free stochastic optimization for additive models A. Akhavan Alexandre B. Tsybakov 26 0 0 03 Mar 2025
Faster WIND: Accelerating Iterative Best-of- $N$ Distillation for LLM Alignment Tong Yang Jincheng Mei H. Dai Zixin Wen Shicong Cen Dale Schuurmans Yuejie Chi Bo Dai 43 4 0 20 Feb 2025
Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals Alexander Mielke Jia Jie Zhu 56 1 0 28 Jan 2025
Convergence Analysis of the Wasserstein Proximal Algorithm beyond Geodesic Convexity Shuailong Zhu Xiaohui Chen 74 0 0 28 Jan 2025
A Regularized Online Newton Method for Stochastic Convex Bandits with Linear Vanishing Noise Jingxin Zhan Yuchen Xin Kaicheng Jin Zhihua Zhang 27 0 0 19 Jan 2025
Non-geodesically-convex optimization in the Wasserstein space Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Petrus Mikkola Marcelo Hartmann Kai Puolamaki Arto Klami 53 2 0 08 Jan 2025
FedRLHF: A Convergence-Guaranteed Federated Framework for Privacy-Preserving and Personalized RLHF Flint Xiaofeng Fan Cheston Tan Yew-Soon Ong Roger Wattenhofer Wei Tsang Ooi 80 1 0 20 Dec 2024
S-CFE: Simple Counterfactual Explanations Shpresim Sadiku Moritz Wagner Sai Ganesh Nagarajan S. Pokutta 26 0 0 21 Oct 2024
Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late in Training Zhanpeng Zhou Mingze Wang Yuchen Mao Bingrui Li Junchi Yan AAML 57 0 0 14 Oct 2024
Nesterov acceleration in benignly non-convex landscapes Kanan Gupta Stephan Wojtowytsch 34 2 0 10 Oct 2024
Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference Qining Zhang Lei Ying OffRL 37 2 0 25 Sep 2024
Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions Siqiao Mu Diego Klabjan MU 50 3 0 15 Sep 2024
Mask in the Mirror: Implicit Sparsification Tom Jacobs R. Burkholz 40 3 0 19 Aug 2024
An Adaptive Stochastic Gradient Method with Non-negative Gauss-Newton Stepsizes Antonio Orvieto Lin Xiao 37 2 0 05 Jul 2024
Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim Joohwan Ko Yian Ma Jacob R. Gardner 48 0 0 03 Jun 2024
Fast Two-Time-Scale Stochastic Gradient Method with Applications in Reinforcement Learning Sihan Zeng Thinh T. Doan 49 5 0 15 May 2024
Learning Optimal Deterministic Policies with Stochastic Policy Gradients Alessandro Montenegro Marco Mussi Alberto Maria Metelli Matteo Papini 38 2 0 03 May 2024
Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand Slawek Smyl Boris N. Oreshkin Paweł Pełka Grzegorz Dudek AI4TS 32 0 0 26 Apr 2024
Understanding and Improving Training-free Loss-based Diffusion Guidance Yifei Shen Xinyang Jiang Yezhen Wang Yifan Yang Dongqi Han Dongsheng Li FaML 21 5 0 19 Mar 2024
Directional Smoothness and Gradient Methods: Convergence and Adaptivity Aaron Mishkin Ahmed Khaled Yuanhao Wang Aaron Defazio Robert Mansel Gower 36 6 0 06 Mar 2024
Level Set Teleportation: An Optimization Perspective Aaron Mishkin A. Bietti Robert Mansel Gower 28 1 0 05 Mar 2024
Non-convergence to global minimizers for Adam and stochastic gradient descent optimization and constructions of local minimizers in the training of artificial neural networks Arnulf Jentzen Adrian Riekert 33 4 0 07 Feb 2024
Careful with that Scalpel: Improving Gradient Surgery with an EMA Yu-Guan Hsieh James Thornton Eugène Ndiaye Michal Klein Marco Cuturi Pierre Ablin MedIm 31 0 0 05 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 19 5 0 02 Feb 2024
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications R. Karandikar M. Vidyasagar 25 7 0 05 Dec 2023
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach Kai Li Jingjing Zheng Xinnan Yuan W. Ni Ozgur B. Akan H. Vincent Poor AAML 10 15 0 30 Nov 2023
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 39 1 0 29 Nov 2023
A Large Deviations Perspective on Policy Gradient Algorithms Wouter Jongeneel Daniel Kuhn Mengmeng Li 11 1 0 13 Nov 2023
Adaptive Mirror Descent Bilevel Optimization Feihu Huang 28 1 0 08 Nov 2023
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods A. Ma Yangchen Pan Amir-massoud Farahmand AAML 25 5 0 13 Aug 2023
Analyzing and Improving Greedy 2-Coordinate Updates for Equality-Constrained Optimization via Steepest Descent in the 1-Norm A. Ramesh Aaron Mishkin Mark W. Schmidt Yihan Zhou J. Lavington Jennifer She 24 1 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 24 10 0 23 Jun 2023
Distributed Random Reshuffling Methods with Improved Convergence Kun-Yen Huang Linli Zhou Shi Pu 24 4 0 21 Jun 2023
Achieving Consensus over Compact Submanifolds Jiang Hu Jiaojiao Zhang Kangkang Deng 23 3 0 07 Jun 2023
Minimum intrinsic dimension scaling for entropic optimal transport Austin J. Stromme 18 10 0 06 Jun 2023
How to escape sharp minima with random perturbations Kwangjun Ahn Ali Jadbabaie S. Sra ODL 24 6 0 25 May 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 21 6 0 08 Mar 2023
On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level Feihu Huang 19 18 0 07 Mar 2023
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization Feihu Huang Chunyu Xuan Xinrui Wang Siqi Zhang Songcan Chen 26 7 0 07 Mar 2023
Fast and Interpretable Dynamics for Fisher Markets via Block-Coordinate Updates Tianlong Nan Yuan Gao Christian Kroer 17 2 0 01 Mar 2023
From Optimization to Sampling Through Gradient Flows Nicolas García Trillos B. Hosseini D. Sanz-Alonso 15 11 0 22 Feb 2023
A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee Mo Zhou Jian-Xiong Lu 23 7 0 11 Feb 2023
DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule Maor Ivgi Oliver Hinder Y. Carmon ODL 24 56 0 08 Feb 2023
Distributed Stochastic Optimization under a General Variance Condition Kun-Yen Huang Xiao Li Shin-Yi Pu FedML 30 5 0 30 Jan 2023
Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering Rui Zhu Di Tang Siyuan Tang Guanhong Tao Shiqing Ma XiaoFeng Wang Haixu Tang DD 11 3 0 29 Jan 2023