Strength of Minibatch Noise in SGD

Strength of Minibatch Noise in SGD

10 February 2021

Papers citing "Strength of Minibatch Noise in SGD"

11 / 11 papers shown

Title
Correlated Noise in Epoch-Based Stochastic Gradient Descent: Implications for Weight Variances Marcel Kühn B. Rosenow 21 3 0 08 Jun 2023
On a continuous time model of gradient descent dynamics and instability in deep learning Mihaela Rosca Yan Wu Chongli Qin Benoit Dherin 23 7 0 03 Feb 2023
On the Lipschitz Constant of Deep Networks and Double Descent Matteo Gamba Hossein Azizpour Mårten Björkman 33 7 0 28 Jan 2023
Training trajectories, mini-batch losses and the curious role of the learning rate Mark Sandler A. Zhmoginov Max Vladymyrov Nolan Miller ODL 28 10 0 05 Jan 2023
On the Overlooked Structure of Stochastic Gradients Zeke Xie Qian-Yuan Tang Mingming Sun P. Li 33 6 0 05 Dec 2022
Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States Ziqiao Wang Yongyi Mao 30 10 0 19 Nov 2022
Noise Injection Node Regularization for Robust Learning N. Levi I. Bloch M. Freytsis T. Volansky AI4CE 32 2 0 27 Oct 2022
SGD with Large Step Sizes Learns Sparse Features Maksym Andriushchenko Aditya Varre Loucas Pillaud-Vivien Nicolas Flammarion 45 56 0 11 Oct 2022
Stochastic Neural Networks with Infinite Width are Deterministic Liu Ziyin Hanlin Zhang Xiangming Meng Yuting Lu Eric P. Xing Masakuni Ueda 34 3 0 30 Jan 2022
The large learning rate phase of deep learning: the catapult mechanism Aitor Lewkowycz Yasaman Bahri Ethan Dyer Jascha Narain Sohl-Dickstein Guy Gur-Ari ODL 159 235 0 04 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015