Tackling benign nonconvexity with smoothing and stochastic gradients

18 February 2022

Papers citing "Tackling benign nonconvexity with smoothing and stochastic gradients"

6 / 6 papers shown

Title
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy Anastasia Koloskova Ryan McKenna Zachary B. Charles Keith Rush Brendan McMahan 27 8 0 02 Feb 2023
EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression Kaja Gruntkowska A. Tyurin Peter Richtárik 36 21 0 30 Sep 2022
Special Properties of Gradient Descent with Large Learning Rates Amirkeivan Mohtashami Martin Jaggi Sebastian U. Stich MLT 21 7 0 30 May 2022
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,878 0 15 Sep 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 119 1,194 0 16 Aug 2016
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 111 259 0 10 Dec 2012