Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems

10 July 2014

Papers citing "Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems"

29 / 29 papers shown

Title
A Coefficient Makes SVRG Effective Yida Yin Zhiqiu Xu Zhiyuan Li Trevor Darrell Zhuang Liu 33 1 0 09 Nov 2023
SPIRAL: A superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization Pourya Behmandpoor P. Latafat Andreas Themelis Marc Moonen Panagiotis Patrinos 29 2 0 17 Jul 2022
Federated Random Reshuffling with Compression and Variance Reduction Grigory Malinovsky Peter Richtárik FedML 27 10 0 08 May 2022
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 32 0 0 26 Aug 2020
Federated Stochastic Gradient Langevin Dynamics Khaoula El Mekkaoui Diego Mesquita P. Blomstedt Samuel Kaski FedML 19 24 0 23 Apr 2020
A Unified Convergence Analysis for Shuffling-Type Gradient Methods Lam M. Nguyen Quoc Tran-Dinh Dzung Phan Phuong Ha Nguyen Marten van Dijk 39 78 0 19 Feb 2020
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization Samuel Horváth Lihua Lei Peter Richtárik Michael I. Jordan 57 30 0 13 Feb 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems Filip Hanzely D. Kovalev Peter Richtárik 35 17 0 11 Feb 2020
A Unifying Framework for Variance Reduction Algorithms for Finding Zeroes of Monotone Operators Xun Zhang W. Haskell Z. Ye 4 3 0 22 Jun 2019
Cocoercivity, Smoothness and Bias in Variance-Reduced Stochastic Gradient Methods Martin Morin Pontus Giselsson 20 2 0 21 Mar 2019
On the Ineffectiveness of Variance Reduced Optimization for Deep Learning Aaron Defazio Léon Bottou UQCV DRL 21 112 0 11 Dec 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 25 146 0 20 Jun 2018
Stochastic Variance-Reduced Policy Gradient Matteo Papini Damiano Binaghi Giuseppe Canonaco Matteo Pirotta Marcello Restelli 16 174 0 14 Jun 2018
Analysis of Biased Stochastic Gradient Descent Using Sequential Semidefinite Programs Bin Hu Peter M. Seiler Laurent Lessard 16 38 0 03 Nov 2017
Variance-Reduced Stochastic Learning under Random Reshuffling Bicheng Ying Kun Yuan Ali H. Sayed 23 13 0 04 Aug 2017
A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints Bin Hu Peter M. Seiler Anders Rantzer 22 35 0 25 Jun 2017
Stochastic Recursive Gradient Algorithm for Nonconvex Optimization Lam M. Nguyen Jie Liu K. Scheinberg Martin Takáč 6 94 0 20 May 2017
Big Batch SGD: Automated Inference using Adaptive Batch Sizes Soham De A. Yadav David Jacobs Tom Goldstein ODL 14 62 0 18 Oct 2016
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure A. Bietti Julien Mairal 44 36 0 04 Oct 2016
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration Hongzhou Lin Julien Mairal Zaïd Harchaoui 23 13 0 04 Oct 2016
Trading-off variance and complexity in stochastic gradient descent Vatsal Shah Megasthenis Asteris Anastasios Kyrillidis Sujay Sanghavi 17 13 0 22 Mar 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 15 575 0 18 Mar 2016
Variance Reduction for Faster Non-Convex Optimization Zeyuan Allen-Zhu Elad Hazan ODL 16 390 0 17 Mar 2016
A Simple Practical Accelerated Method for Finite Sums Aaron Defazio 20 120 0 08 Feb 2016
New Optimisation Methods for Machine Learning Aaron Defazio 38 6 0 09 Oct 2015
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 35 194 0 23 Jun 2015
SDCA without Duality Shai Shalev-Shwartz 25 47 0 22 Feb 2015
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 79 317 0 18 Feb 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark W. Schmidt Nicolas Le Roux Francis R. Bach 55 1,243 0 10 Sep 2013