Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems

12 July 2017

Papers citing "Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems"

12 / 12 papers shown

Title
Some Primal-Dual Theory for Subgradient Methods for Strongly Convex Optimization Benjamin Grimmer Danlin Li 67 6 0 31 Dec 2024
Towards Certified Unlearning for Deep Neural Networks Binchi Zhang Yushun Dong Tianhao Wang Wenlin Yao MU 84 8 0 01 Aug 2024
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 81 572 0 04 Jul 2018
Stochastic model-based minimization of weakly convex functions Damek Davis Dmitriy Drusvyatskiy 66 373 0 17 Mar 2018
$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 Damek Davis Dmitriy Drusvyatskiy 53 101 0 08 Feb 2018
Catalyst Acceleration for Gradient-Based Non-Convex Optimization Courtney Paquette Hongzhou Lin Dmitriy Drusvyatskiy Julien Mairal Zaïd Harchaoui ODL 40 40 0 31 Mar 2017
A SMART Stochastic Algorithm for Nonconvex Optimization with Applications to Robust Machine Learning Aleksandr Aravkin Damek Davis 59 21 0 04 Oct 2016
Accelerating Stochastic Composition Optimization Mengdi Wang Ji Liu Ethan X. Fang 49 147 0 25 Jul 2016
Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions Mengdi Wang Ethan X. Fang Han Liu 79 261 0 14 Nov 2014
Block stochastic gradient iteration for convex and nonconvex optimization Yangyang Xu W. Yin 121 134 0 12 Aug 2014
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 90 1,538 0 22 Sep 2013
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 163 260 0 10 Dec 2012