On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications

7 October 2021

Papers citing "On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications"

7 / 7 papers shown

Title
Information-Theoretic Generalization Bounds for Deep Neural Networks Haiyun He Christina Lee Yu 27 4 0 04 Apr 2024
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 36 1 0 08 Nov 2023
Tighter Information-Theoretic Generalization Bounds from Supersamples Ziqiao Wang Yongyi Mao 13 17 0 05 Feb 2023
Towards Understanding Sharpness-Aware Minimization Maksym Andriushchenko Nicolas Flammarion AAML 6 131 0 13 Jun 2022
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates Jeffrey Negrea Mahdi Haghifam Gintare Karolina Dziugaite Ashish Khisti Daniel M. Roy FedML 105 146 0 06 Nov 2019
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 2,696 0 15 Sep 2016
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 111 551 0 27 Feb 2015