Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization

26 September 2011

Papers citing "Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization"

14 / 14 papers shown

Title
HOME-3: High-Order Momentum Estimator with Third-Power Gradient for Convex and Smooth Nonconvex Optimization Wei Zhang Arif Hassan Zidan Afrar Jahin Wei Zhang Tianming Liu ODL 45 0 0 16 May 2025
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization Tianyi Lin Chi Jin Michael I. Jordan 77 8 0 28 Jan 2025
Some Primal-Dual Theory for Subgradient Methods for Strongly Convex Optimization Benjamin Grimmer Danlin Li 63 6 0 31 Dec 2024
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis Zhijie Chen Qiaobo Li A. Banerjee FedML 51 0 0 11 Nov 2024
Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees Aleksandar Armacki Shuhua Yu Pranay Sharma Gauri Joshi Dragana Bajović D. Jakovetić S. Kar 81 2 0 17 Oct 2024
Collaborative and Efficient Personalization with Mixtures of Adaptors Abdulla Jasem Almansoori Samuel Horváth Martin Takáč FedML 66 3 0 04 Oct 2024
Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance Dimitris Oikonomou Nicolas Loizou 64 5 0 06 Jun 2024
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning S. Samsonov Eric Moulines Qi-Man Shao Zhuo-Song Zhang Alexey Naumov 63 5 0 26 May 2024
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better En-hao Liu Junyi Zhu Zinan Lin Xuefei Ning Shuaiqi Wang ... Sergey Yekhanin Guohao Dai Huazhong Yang Yu Wang Yu Wang MoMe 92 4 0 02 Apr 2024
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality Ziyang Wei Wanrong Zhu Wei Biao Wu 50 5 0 13 Jul 2023
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization Florian E. Dorner Nikola Konstantinov Georgi Pashaliev Martin Vechev FedML 54 6 0 25 May 2023
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 65 37 0 24 Sep 2021
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation Robert Mansel Gower Othmane Sebbouh Nicolas Loizou 67 75 0 18 Jun 2020
Stochastic Optimization for Performative Prediction Celestine Mendler-Dünner Juan C. Perdomo Tijana Zrnic Moritz Hardt 32 114 0 12 Jun 2020