A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks

18 January 2019

Papers citing "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"

7 / 57 papers shown

Title
Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks Umut Simsekli Ozan Sener George Deligiannidis Murat A. Erdogdu 44 55 0 16 Jun 2020
Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization S. Chatterjee ODL OOD 11 48 0 25 Feb 2020
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima Zeke Xie Issei Sato Masashi Sugiyama ODL 28 17 0 10 Feb 2020
Non-Gaussianity of Stochastic Gradient Noise A. Panigrahi Raghav Somani Navin Goyal Praneeth Netrapalli 23 52 0 21 Oct 2019
On the Noisy Gradient Descent that Generalizes as SGD Jingfeng Wu Wenqing Hu Haoyi Xiong Jun Huan Vladimir Braverman Zhanxing Zhu MLT 24 10 0 18 Jun 2019
Continuous-time Models for Stochastic Optimization Algorithms Antonio Orvieto Aurelien Lucchi 19 31 0 05 Oct 2018
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 308 2,890 0 15 Sep 2016