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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
On the Relevance of Byzantine Robust Optimization Against Data Poisoning Sadegh Farhadkhani R. Guerraoui Nirupam Gupta Rafael Pinot AAML 96 2 0 01 May 2024
Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand Slawek Smyl Boris N. Oreshkin Paweł Pełka Grzegorz Dudek AI4TS 96 1 0 26 Apr 2024
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey Feng Liang Zhen Zhang Haifeng Lu Victor C. M. Leung Yanyi Guo Xiping Hu GNN 133 11 0 09 Apr 2024
Revisiting Random Weight Perturbation for Efficiently Improving Generalization Tao Li Qinghua Tao Weihao Yan Zehao Lei Yingwen Wu Kun Fang Mingzhen He Xiaolin Huang AAML 157 7 0 30 Mar 2024
The Effectiveness of Local Updates for Decentralized Learning under Data Heterogeneity Tongle Wu Ying Sun 85 2 0 23 Mar 2024
Understanding and Improving Training-free Loss-based Diffusion Guidance Yifei Shen Xinyang Jiang Yezhen Wang Yifan Yang Dongqi Han Dongsheng Li FaML 136 16 0 19 Mar 2024
Friendly Sharpness-Aware Minimization Tao Li Pan Zhou Zhengbao He Xinwen Cheng Xiaolin Huang AAML 116 23 0 19 Mar 2024
Directional Smoothness and Gradient Methods: Convergence and Adaptivity Aaron Mishkin Ahmed Khaled Yuanhao Wang Aaron Defazio Robert Mansel Gower 180 12 0 06 Mar 2024
Level Set Teleportation: An Optimization Perspective Aaron Mishkin A. Bietti Robert Mansel Gower 137 1 0 05 Mar 2024
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities Rocco Caprio Juan Kuntz Samuel Power A. M. Johansen 137 10 0 04 Mar 2024
From Inverse Optimization to Feasibility to ERM Saurabh Mishra Anant Raj Sharan Vaswani 103 3 0 27 Feb 2024
Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence Ilyas Fatkhullin Niao He 88 7 0 27 Feb 2024
Investigating Deep Watermark Security: An Adversarial Transferability Perspective Biqing Qi Junqi Gao Yiang Luo Jianxing Liu Ligang Wu Bowen Zhou AAML 106 4 0 26 Feb 2024
A Lower Bound for Estimating Fréchet Means Shayan Hundrieser B. Eltzner S. Huckemann 61 2 0 19 Feb 2024
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization Andrew Lowy Jonathan R. Ullman Stephen J. Wright 139 10 0 17 Feb 2024
An Accelerated Distributed Stochastic Gradient Method with Momentum Kun-Yen Huang Shi Pu Angelia Nedić 113 11 0 15 Feb 2024
Differentially Private Zeroth-Order Methods for Scalable Large Language Model Finetuning Zhicheng Liu Jian Lou Wenxuan Bao Yihan Hu Baochun Li Zhan Qin K. Ren 164 11 0 12 Feb 2024
Towards Quantifying the Preconditioning Effect of Adam Rudrajit Das Naman Agarwal Sujay Sanghavi Inderjit S. Dhillon 49 7 0 11 Feb 2024
Federated Learning Can Find Friends That Are Advantageous N. Tupitsa Samuel Horváth Martin Takávc Eduard A. Gorbunov FedML 147 2 0 07 Feb 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 81 5 0 07 Feb 2024
Optimal sampling for stochastic and natural gradient descent Robert Gruhlke A. Nouy Philipp Trunschke 82 3 0 05 Feb 2024
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation Sobihan Surendran Antoine Godichon-Baggioni Adeline Fermanian Sylvain Le Corff 172 2 0 05 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 126 1 0 05 Feb 2024
On the Complexity of Finite-Sum Smooth Optimization under the Polyak-Łojasiewicz Condition Yunyan Bai Yuxing Liu Luo Luo 92 1 0 04 Feb 2024
Challenges in Training PINNs: A Loss Landscape Perspective Pratik Rathore Weimu Lei Zachary Frangella Lu Lu Madeleine Udell AI4CE PINN ODL 137 70 0 02 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 178 6 0 02 Feb 2024
Behind the Myth of Exploration in Policy Gradients Adrien Bolland Gaspard Lambrechts Damien Ernst 192 1 0 31 Jan 2024
Diffusion Stochastic Optimization for Min-Max Problems H. Cai Sulaiman A. Alghunaim Ali H. Sayed 101 3 0 26 Jan 2024
Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space Mingyang Yi Bohan Wang 132 0 0 24 Jan 2024
Efficient Learning in Polyhedral Games via Best Response Oracles Darshan Chakrabarti Gabriele Farina Christian Kroer 80 4 0 06 Dec 2023
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications Rajeeva Laxman Karandikar M. Vidyasagar 108 11 0 05 Dec 2023
A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization Junwen Qiu Xiao Li Andre Milzarek 181 3 0 02 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 105 19 0 30 Nov 2023
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 315 2 0 29 Nov 2023
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach Xinwei Zhang Zhiqi Bu Zhiwei Steven Wu Mingyi Hong 98 9 0 24 Nov 2023
Locally Optimal Descent for Dynamic Stepsize Scheduling Gilad Yehudai Alon Cohen Amit Daniely Yoel Drori Tomer Koren Mariano Schain 130 0 0 23 Nov 2023
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates Michael Menart Enayat Ullah Raman Arora Raef Bassily Cristóbal Guzmán 109 2 0 22 Nov 2023
Non-Uniform Smoothness for Gradient Descent A. Berahas Lindon Roberts Fred Roosta 102 4 0 15 Nov 2023
A Large Deviations Perspective on Policy Gradient Algorithms Wouter Jongeneel Daniel Kuhn Mengmeng Li 106 1 0 13 Nov 2023
Adaptive Mirror Descent Bilevel Optimization Feihu Huang 151 1 0 08 Nov 2023
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization Wei Shen Minhui Huang Jiawei Zhang Cong Shen FedML 164 3 0 02 Nov 2023
AdaSub: Stochastic Optimization Using Second-Order Information in Low-Dimensional Subspaces João Victor Galvão da Mata Martin S. Andersen 68 1 0 30 Oct 2023
Controlled Decoding from Language Models Sidharth Mudgal Jong Lee H. Ganapathy Yaguang Li Tao Wang ... Michael Collins Trevor Strohman Jilin Chen Alex Beutel Ahmad Beirami 208 98 0 25 Oct 2023
DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset Weijie Liu Xiaoxi Zhang Jingpu Duan Carlee Joe-Wong Zhi Zhou Xu Chen 97 15 0 20 Oct 2023
A connection between Tempering and Entropic Mirror Descent Nicolas Chopin F. R. Crucinio Anna Korba 123 15 0 18 Oct 2023
DPZero: Private Fine-Tuning of Language Models without Backpropagation Liang Zhang Bingcong Li K. K. Thekumparampil Sewoong Oh Niao He 140 16 0 14 Oct 2023
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity Youssef Allouah R. Guerraoui Nirupam Gupta Rafael Pinot Geovani Rizk OOD 96 19 0 24 Sep 2023
Distributionally Time-Varying Online Stochastic Optimization under Polyak-Łojasiewicz Condition with Application in Conditional Value-at-Risk Statistical Learning Yuen-Man Pun Farhad Farokhi Iman Shames 87 3 0 18 Sep 2023
Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity and Last-Iterate Convergence Jiduan Wu Anas Barakat Ilyas Fatkhullin Niao He 233 7 0 08 Sep 2023
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation Jeongyeol Kwon Dohyun Kwon Steve Wright Robert D. Nowak 146 37 0 04 Sep 2023