Non-Uniform Stochastic Average Gradient Method for Training Conditional
Random Fields

Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields

16 April 2015

Reza Babanezhad

Mohamed Osama Ahmed

Papers citing "Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields"

19 / 19 papers shown

Title
L-DQN: An Asynchronous Limited-Memory Distributed Quasi-Newton Method Bugra Can Saeed Soori M. Dehnavi Mert Gurbuzbalaban 45 2 0 20 Aug 2021
Structured Convolutional Kernel Networks for Airline Crew Scheduling Yassine Yaakoubi F. Soumis Simon Lacoste-Julien AI4TS 26 10 0 25 May 2021
SVRG Meets AdaGrad: Painless Variance Reduction Benjamin Dubois-Taine Sharan Vaswani Reza Babanezhad Mark Schmidt Simon Lacoste-Julien 23 18 0 18 Feb 2021
Variance-Reduced Methods for Machine Learning Robert Mansel Gower Mark Schmidt Francis R. Bach Peter Richtárik 24 112 0 02 Oct 2020
Sampling and Update Frequencies in Proximal Variance-Reduced Stochastic Gradient Methods Martin Morin Pontus Giselsson 27 4 0 13 Feb 2020
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates Sharan Vaswani Aaron Mishkin I. Laradji Mark Schmidt Gauthier Gidel Simon Lacoste-Julien ODL 41 205 0 24 May 2019
Cocoercivity, Smoothness and Bias in Variance-Reduced Stochastic Gradient Methods Martin Morin Pontus Giselsson 20 2 0 21 Mar 2019
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise A. Kulunchakov Julien Mairal 34 44 0 25 Jan 2019
SAGA with Arbitrary Sampling Xun Qian Zheng Qu Peter Richtárik 37 25 0 24 Jan 2019
A Universally Optimal Multistage Accelerated Stochastic Gradient Method N. Aybat Alireza Fallah Mert Gurbuzbalaban Asuman Ozdaglar ODL 24 57 0 23 Jan 2019
Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields Rémi Le Priol Alexandre Piché Simon Lacoste-Julien 28 5 0 22 Dec 2017
Safe Adaptive Importance Sampling Sebastian U. Stich Anant Raj Martin Jaggi 35 54 0 07 Nov 2017
Determinantal Point Processes for Mini-Batch Diversification Cheng Zhang Hedvig Kjellström Stephan Mandt 27 35 0 01 May 2017
Coupling Adaptive Batch Sizes with Learning Rates Lukas Balles Javier Romero Philipp Hennig ODL 21 110 0 15 Dec 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 71 1,877 0 08 Oct 2016
Stochastic Variance Reduction Methods for Saddle-Point Problems B. Palaniappan Francis R. Bach 18 210 0 20 May 2016
Online Batch Selection for Faster Training of Neural Networks I. Loshchilov Frank Hutter ODL 41 298 0 19 Nov 2015
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 93 737 0 19 Mar 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 114 1,244 0 10 Sep 2013