On exponential convergence of SGD in non-convex over-parametrized learning

6 November 2018

Papers citing "On exponential convergence of SGD in non-convex over-parametrized learning"

12 / 12 papers shown

Title
Nesterov acceleration in benignly non-convex landscapes Kanan Gupta Stephan Wojtowytsch 34 2 0 10 Oct 2024
Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation Aaron Mishkin Mert Pilanci Mark Schmidt 62 1 0 03 Apr 2024
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 39 1 0 29 Nov 2023
Fast Convergence in Learning Two-Layer Neural Networks with Separable Data Hossein Taheri Christos Thrampoulidis MLT 16 3 0 22 May 2023
Stochastic Ratios Tracking Algorithm for Large Scale Machine Learning Problems Shigeng Sun Yuchen Xie 13 3 0 17 May 2023
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion G. Zhang Hong-Ming Chiu Richard Y. Zhang 16 10 0 24 Aug 2022
Benchmark Assessment for DeepSpeed Optimization Library G. Liang I. Alsmadi 24 3 0 12 Feb 2022
Stochastic gradient descent with noise of machine learning type. Part I: Discrete time analysis Stephan Wojtowytsch 21 50 0 04 May 2021
Convergence of stochastic gradient descent schemes for Lojasiewicz-landscapes Steffen Dereich Sebastian Kassing 26 27 0 16 Feb 2021
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani Francis R. Bach Mark W. Schmidt 17 296 0 16 Oct 2018
Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate Mor Shpigel Nacson Nathan Srebro Daniel Soudry FedML MLT 11 97 0 05 Jun 2018
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 121 1,198 0 16 Aug 2016