v1v2v3v4 (latest)

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 / 588 papers shown

Title
Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence Ilyas Fatkhullin Niao He 68 4 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 54 3 0 26 Feb 2024
A Lower Bound for Estimating Fréchet Means Shayan Hundrieser B. Eltzner S. Huckemann 44 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 95 8 0 17 Feb 2024
An Accelerated Distributed Stochastic Gradient Method with Momentum Kun-Yen Huang Shi Pu Angelia Nedić 81 10 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 120 10 0 12 Feb 2024
Towards Quantifying the Preconditioning Effect of Adam Rudrajit Das Naman Agarwal Sujay Sanghavi Inderjit S. Dhillon 30 7 0 11 Feb 2024
Federated Learning Can Find Friends That Are Advantageous N. Tupitsa Samuel Horváth Martin Takávc Eduard A. Gorbunov FedML 97 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 61 4 0 07 Feb 2024
Optimal sampling for stochastic and natural gradient descent Robert Gruhlke A. Nouy Philipp Trunschke 57 3 0 05 Feb 2024
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation Sobihan Surendran Antoine Godichon-Baggioni Adeline Fermanian Sylvain Le Corff 100 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 77 0 0 05 Feb 2024
On the Complexity of Finite-Sum Smooth Optimization under the Polyak-Łojasiewicz Condition Yunyan Bai Yuxing Liu Luo Luo 57 0 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 105 53 0 02 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 103 5 0 02 Feb 2024
Diffusion Stochastic Optimization for Min-Max Problems H. Cai Sulaiman A. Alghunaim Ali H. Sayed 69 2 0 26 Jan 2024
Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space Mingyang Yi Bohan Wang 56 0 0 24 Jan 2024
Efficient Learning in Polyhedral Games via Best Response Oracles Darshan Chakrabarti Gabriele Farina Christian Kroer 62 4 0 06 Dec 2023
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications Rajeeva Laxman Karandikar M. Vidyasagar 46 10 0 05 Dec 2023
A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization Junwen Qiu Xiao Li Andre Milzarek 93 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 80 16 0 30 Nov 2023
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 156 2 0 29 Nov 2023
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach Xinwei Zhang Zhiqi Bu Zhiwei Steven Wu Mingyi Hong 52 7 0 24 Nov 2023
Locally Optimal Descent for Dynamic Stepsize Scheduling Gilad Yehudai Alon Cohen Amit Daniely Yoel Drori Tomer Koren Mariano Schain 84 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 86 2 0 22 Nov 2023
Non-Uniform Smoothness for Gradient Descent A. Berahas Lindon Roberts Fred Roosta 93 4 0 15 Nov 2023
A Large Deviations Perspective on Policy Gradient Algorithms Wouter Jongeneel Daniel Kuhn Mengmeng Li 55 1 0 13 Nov 2023
Adaptive Mirror Descent Bilevel Optimization Feihu Huang 107 1 0 08 Nov 2023
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization Wei Shen Minhui Huang Jiawei Zhang Cong Shen FedML 94 2 0 02 Nov 2023
AdaSub: Stochastic Optimization Using Second-Order Information in Low-Dimensional Subspaces João Victor Galvão da Mata Martin S. Andersen 31 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 112 91 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 73 9 0 20 Oct 2023
A connection between Tempering and Entropic Mirror Descent Nicolas Chopin F. R. Crucinio Anna Korba 49 14 0 18 Oct 2023
DPZero: Private Fine-Tuning of Language Models without Backpropagation Liang Zhang Bingcong Li K. K. Thekumparampil Sewoong Oh Niao He 92 15 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 80 18 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 17 2 0 18 Sep 2023
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation Jeongyeol Kwon Dohyun Kwon Steve Wright Robert D. Nowak 93 30 0 04 Sep 2023
A Unified Analysis for the Subgradient Methods Minimizing Composite Nonconvex, Nonsmooth and Non-Lipschitz Functions Daoli Zhu Lei Zhao Shuzhong Zhang 101 2 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 44 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 50 2 0 21 Aug 2023
Variance reduction techniques for stochastic proximal point algorithms Cheik Traoré Vassilis Apidopoulos Saverio Salzo S. Villa 64 5 0 18 Aug 2023
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods A. Ma Yangchen Pan Amir-massoud Farahmand AAML 61 7 0 13 Aug 2023
Faster Stochastic Algorithms for Minimax Optimization under Polyak--Łojasiewicz Conditions Le‐Yu Chen Boyuan Yao Luo Luo 64 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 74 9 0 20 Jul 2023
Zero-th Order Algorithm for Softmax Attention Optimization Yichuan Deng Zhihang Li Sridhar Mahadevan Zhao Song 62 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 58 0 0 14 Jul 2023
Invex Programs: First Order Algorithms and Their Convergence Adarsh Barik S. Sra Jean Honorio 58 2 0 10 Jul 2023
Fairness-aware Federated Minimax Optimization with Convergence Guarantee Gerry Windiarto Mohamad Dunda Shenghui Song FedML 56 2 0 10 Jul 2023
Accelerated Optimization Landscape of Linear-Quadratic Regulator Le Feng Yuan‐Hua Ni 63 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 62 1 0 03 Jul 2023