Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise

14 February 2023

Papers citing "Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise"

8 / 8 papers shown

Title
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 74 2 0 17 Oct 2024
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks Umut Simsekli Mert Gurbuzbalaban T. H. Nguyen G. Richard Levent Sagun 41 56 0 29 Nov 2019
Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization Quoc Tran-Dinh Nhan H. Pham Dzung Phan Lam M. Nguyen 43 55 0 15 May 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks Umut Simsekli Levent Sagun Mert Gurbuzbalaban 67 241 0 18 Jan 2019
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 79 572 0 04 Jul 2018
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 79 1,817 0 01 Jul 2014
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 41 1,538 0 22 Sep 2013
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 67 1,031 0 10 Sep 2012