Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification

12 October 2016

Papers citing "Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification"

8 / 8 papers shown

Title
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift Alekh Agarwal Sham Kakade J. Lee G. Mahajan 11 315 0 01 Aug 2019
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares Rong Ge Sham Kakade Rahul Kidambi Praneeth Netrapalli 23 149 0 29 Apr 2019
The Effect of Network Width on the Performance of Large-batch Training Lingjiao Chen Hongyi Wang Jinman Zhao Dimitris Papailiopoulos Paraschos Koutris 13 22 0 11 Jun 2018
On the insufficiency of existing momentum schemes for Stochastic Optimization Rahul Kidambi Praneeth Netrapalli Prateek Jain Sham Kakade ODL 19 117 0 15 Mar 2018
Iterate averaging as regularization for stochastic gradient descent Gergely Neu Lorenzo Rosasco MoMe 32 61 0 22 Feb 2018
Exponential convergence of testing error for stochastic gradient methods Loucas Pillaud-Vivien Alessandro Rudi Francis R. Bach 24 31 0 13 Dec 2017
Stochastic Composite Least-Squares Regression with convergence rate O(1/n) Nicolas Flammarion Francis R. Bach 24 27 0 21 Feb 2017
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 177 683 0 07 Dec 2010