Towards stability and optimality in stochastic gradient descent

10 May 2015

Papers citing "Towards stability and optimality in stochastic gradient descent"

10 / 10 papers shown

Title
Online estimation of the inverse of the Hessian for stochastic optimization with application to universal stochastic Newton algorithms Antoine Godichon-Baggioni Wei Lu Bruno Portier 44 1 0 15 Jan 2024
Stable Nonconvex-Nonconcave Training via Linear Interpolation Thomas Pethick Wanyun Xie V. Cevher 35 5 0 20 Oct 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space Michael Diao Krishnakumar Balasubramanian Sinho Chewi Adil Salim BDL 32 21 0 10 Apr 2023
Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks Ye Li Songcan Chen Shengyi Huang PINN 20 3 0 03 Mar 2023
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation Xiao-Tong Yuan P. Li 36 2 0 09 Jan 2023
Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity Hilal Asi John C. Duchi 21 123 0 12 Oct 2018
Stabilized Sparse Online Learning for Sparse Data Yuting Ma Tian Zheng 19 14 0 21 Apr 2016
Stochastic gradient descent methods for estimation with large data sets Dustin Tran Panos Toulis E. Airoldi 12 14 0 22 Sep 2015
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 93 737 0 19 Mar 2014
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 104 572 0 08 Dec 2012