$Stochastic subgradient method converges at the rate $O(k^{-1/4})$ on weakly convex functions$

Stochastic subgradient method converges at the rate $O(k^{-1/4})$ on weakly convex functions

8 February 2018

Papers citing "Stochastic subgradient method converges at the rate $O(k^{-1/4})$ on weakly convex functions"

21 / 21 papers shown

Title
Damped Proximal Augmented Lagrangian Method for weakly-Convex Problems with Convex Constraints Hari Dahal Wei Liu Yangyang Xu 52 5 0 15 Nov 2023
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems Thomas Pethick P. Latafat Panagiotis Patrinos Olivier Fercoq Volkan Cevher 46 45 0 20 Feb 2023
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances Sloan Nietert Ritwik Sadhu Ziv Goldfeld Kengo Kato 43 37 0 17 Oct 2022
Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution Jianhao Ma Salar Fattahi 52 5 0 15 Jul 2022
Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning Alex Gu Songtao Lu Parikshit Ram Tsui-Wei Weng 57 10 0 03 Mar 2022
Large-scale Optimization of Partial AUC in a Range of False Positive Rates Yao Yao Qihang Lin Tianbao Yang 49 16 0 03 Mar 2022
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee Dixian Zhu Gang Li Bokun Wang Xiaodong Wu Tianbao Yang 56 29 0 01 Mar 2022
Outlier-Robust Sparse Estimation via Non-Convex Optimization Yu Cheng Ilias Diakonikolas Rong Ge Shivam Gupta D. Kane Mahdi Soltanolkotabi 52 13 0 23 Sep 2021
An efficient nonconvex reformulation of stagewise convex optimization problems Rudy Bunel Oliver Hinder Srinadh Bhojanapalli Krishnamurthy Dvijotham Dvijotham OffRL 35 14 0 27 Oct 2020
Estimating Barycenters of Measures in High Dimensions Samuel N. Cohen Michael Arbel M. Deisenroth 31 23 0 14 Jul 2020
A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic Mingyi Hong Hoi-To Wai Zhaoran Wang Zhuoran Yang 31 136 0 10 Jul 2020
High-Dimensional Robust Mean Estimation via Gradient Descent Yu Cheng Ilias Diakonikolas Rong Ge Mahdi Soltanolkotabi 24 31 0 04 May 2020
Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization Kenji Kawaguchi Haihao Lu ODL 38 62 0 09 Jul 2019
Efficient Algorithms for Smooth Minimax Optimization K. K. Thekumparampil Prateek Jain Praneeth Netrapalli Sewoong Oh 48 190 0 02 Jul 2019
Stagewise Training Accelerates Convergence of Testing Error Over SGD Zhuoning Yuan Yan Yan Rong Jin Tianbao Yang 60 11 0 10 Dec 2018
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence Yi Tian Xu Qi Qi Qihang Lin Rong Jin Tianbao Yang 37 41 0 28 Nov 2018
Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang 20 107 0 04 Oct 2018
Stochastic model-based minimization under high-order growth Damek Davis Dmitriy Drusvyatskiy Kellie J. MacPhee 14 31 0 01 Jul 2018
Stochastic model-based minimization of weakly convex functions Damek Davis Dmitriy Drusvyatskiy 40 372 0 17 Mar 2018
Stochastic Methods for Composite and Weakly Convex Optimization Problems John C. Duchi Feng Ruan 20 126 0 24 Mar 2017
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark Schmidt Francis R. Bach 132 260 0 10 Dec 2012