Analysis of nonsmooth stochastic approximation: the differential inclusion approach

4 May 2018

Papers citing "Analysis of nonsmooth stochastic approximation: the differential inclusion approach"

10 / 10 papers shown

Title
The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks Sholom Schechtman Nicolas Schreuder 173 0 0 08 Feb 2025
Riemannian Stochastic Approximation for Minimizing Tame Nonsmooth Objective Functions Johannes Aspman Vyacheslav Kungurtsev R. Seraji 26 1 0 31 Dec 2024
Inexact subgradient methods for semialgebraic functions Jérôme Bolte Tam Le Éric Moulines Edouard Pauwels 57 2 0 30 Apr 2024
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization Tianyi Lin Zeyu Zheng Michael I. Jordan 59 52 0 12 Sep 2022
Stochastic Subgradient Descent on a Generic Definable Function Converges to a Minimizer S. Schechtman 22 1 0 06 Sep 2021
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation Kilian Fatras Thibault Séjourné Nicolas Courty Rémi Flamary OT 40 146 0 05 Mar 2021
Minibatch optimal transport distances; analysis and applications Kilian Fatras Younes Zine Szymon Majewski Rémi Flamary Rémi Gribonval Nicolas Courty OT 71 54 0 05 Jan 2021
On Correctness of Automatic Differentiation for Non-Differentiable Functions Wonyeol Lee Hangyeol Yu Xavier Rival Hongseok Yang 20 40 0 12 Jun 2020
A Stochastic Subgradient Method for Distributionally Robust Non-Convex Learning Mert Gurbuzbalaban A. Ruszczynski Landi Zhu 26 9 0 08 Jun 2020
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 90 736 0 19 Mar 2014