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ASAGA: Asynchronous Parallel SAGA

15 June 2016

Papers citing "ASAGA: Asynchronous Parallel SAGA"

50 / 58 papers shown

Title
Asynchronous Decentralized SGD under Non-Convexity: A Block-Coordinate Descent Framework Yijie Zhou Shi Pu 117 0 0 15 May 2025
Distributed Stochastic Gradient Descent with Staleness: A Stochastic Delay Differential Equation Based Framework Siyuan Yu Wei Chen H. V. Poor 277 0 0 17 Jun 2024
Distributed Adaptive Greedy Quasi-Newton Methods with Explicit Non-asymptotic Convergence Bounds Yubo Du Keyou You 194 6 0 30 Nov 2023
Scaling up Stochastic Gradient Descent for Non-convex OptimisationMachine-mediated learning (ML), 2022 S. Mohamad H. Alamri A. Bouchachia 152 3 0 06 Oct 2022
Distributed Dynamic Safe Screening Algorithms for Sparse Regularization Runxue Bao Xidong Wu Wenhan Xian Heng-Chiao Huang 130 1 0 23 Apr 2022
Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping Junya Chen Sijia Wang Lawrence Carin Chenyang Tao 116 3 0 04 Nov 2021
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization Kaiwen Zhou Anthony Man-Cho So James Cheng 150 1 0 30 Sep 2021
Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic GuaranteesJournal of machine learning research (JMLR), 2021 Hamid Reza Feyzmahdavian M. Johansson 183 25 0 09 Sep 2021
L-DQN: An Asynchronous Limited-Memory Distributed Quasi-Newton Method Bugra Can Saeed Soori M. Dehnavi Mert Gurbuzbalaban 192 2 0 20 Aug 2021
Federated Learning with Buffered Asynchronous AggregationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 John Nguyen Kshitiz Malik Hongyuan Zhan Ashkan Yousefpour Michael G. Rabbat Mani Malek Dzmitry Huba FedML 267 385 0 11 Jun 2021
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning Eugene Belilovsky Louis Leconte Lucas Caccia Michael Eickenberg Edouard Oyallon 120 9 0 11 Jun 2021
Pufferfish: Communication-efficient Models At No Extra CostConference on Machine Learning and Systems (MLSys), 2021 Hongyi Wang Saurabh Agarwal Dimitris Papailiopoulos 129 67 0 05 Mar 2021
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable DevicesNeural Information Processing Systems (NeurIPS), 2021 Max Ryabinin Eduard A. Gorbunov Vsevolod Plokhotnyuk Gennady Pekhimenko 296 43 0 04 Mar 2021
Secure Bilevel Asynchronous Vertical Federated Learning with Backward UpdatingAAAI Conference on Artificial Intelligence (AAAI), 2021 Qingsong Zhang Bin Gu Cheng Deng Heng-Chiao Huang FedML 93 77 0 01 Mar 2021
Sum-Rate-Distortion Function for Indirect Multiterminal Source Coding in Federated LearningInternational Symposium on Information Theory (ISIT), 2021 Naifu Zhang M. Tao Jia Wang FedML 202 4 0 21 Jan 2021
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and OptimismJournal of machine learning research (JMLR), 2020 Yu-Guan Hsieh F. Iutzeler J. Malick P. Mertikopoulos AI4CE 253 33 0 21 Dec 2020
Asynchrony and Acceleration in Gossip Algorithms Mathieu Even Aymeric Dieuleveut Laurent Massoulié 212 8 0 04 Nov 2020
Variance-Reduced Methods for Machine LearningProceedings of the IEEE (Proc. IEEE), 2020 Robert Mansel Gower Mark Schmidt Francis R. Bach Peter Richtárik 237 143 0 02 Oct 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 187 0 0 26 Aug 2020
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning Bin Gu An Xu Zhouyuan Huo Cheng Deng Heng-Chiao Huang FedML 167 31 0 14 Aug 2020
Advances in Asynchronous Parallel and Distributed OptimizationProceedings of the IEEE (Proc. IEEE), 2020 By Mahmoud Assran Arda Aytekin Hamid Reza Feyzmahdavian M. Johansson Michael G. Rabbat 178 89 0 24 Jun 2020
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization Chaobing Song Yong Jiang Yi-An Ma 429 24 0 18 Jun 2020
An Optimal Algorithm for Decentralized Finite Sum Optimization Aymeric Dieuleveut Francis R. Bach Laurent Massoulie 187 48 0 20 May 2020
On the Convergence Analysis of Asynchronous SGD for Solving Consistent Linear SystemsLinear Algebra and its Applications (LAA), 2020 Atal Narayan Sahu Aritra Dutta Aashutosh Tiwari Peter Richtárik 179 8 0 05 Apr 2020
Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent Giorgi Nadiradze Ilia Markov Bapi Chatterjee Vyacheslav Kungurtsev Dan Alistarh FedML 211 14 0 16 Jan 2020
ASYNC: A Cloud Engine with Asynchrony and History for Distributed Machine LearningIEEE International Parallel and Distributed Processing Symposium (IPDPS), 2019 Saeed Soori Bugra Can Mert Gurbuzbalaban M. Dehnavi GNN OffRL 222 4 0 19 Jul 2019
A Unifying Framework for Variance Reduction Algorithms for Finding Zeroes of Monotone Operators Xun Zhang W. Haskell Z. Ye 148 3 0 22 Jun 2019
Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1International Conference on Machine Learning, Optimization, and Data Science (MOD), 2019 Majid Jahani M. Nazari S. Rusakov A. Berahas Martin Takávc 186 16 0 30 May 2019
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite SumsNeural Information Processing Systems (NeurIPS), 2019 Aymeric Dieuleveut Francis R. Bach Laurent Massoulie 145 33 0 27 May 2019
Block stochastic gradient descent for large-scale tomographic reconstruction in a parallel network Yushan Gao A. Biguri T. Blumensath 148 3 0 28 Mar 2019
Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems Ehsan Kazemi Liqiang Wang 93 2 0 05 Feb 2019
Asynchronous Accelerated Proximal Stochastic Gradient for Strongly Convex Distributed Finite Sums Aymeric Dieuleveut Francis R. Bach Laurent Massoulié FedML 160 26 0 28 Jan 2019
Decoupled Greedy Learning of CNNs Eugene Belilovsky Michael Eickenberg Edouard Oyallon 284 126 0 23 Jan 2019
Distributed Learning with Sparse Communications by Identification Dmitry Grishchenko F. Iutzeler J. Malick Massih-Reza Amini 129 19 0 10 Dec 2018
Asynchronous Stochastic Composition Optimization with Variance Reduction Shuheng Shen Linli Xu Jingchang Liu Junliang Guo Qing Ling 108 2 0 15 Nov 2018
Distributed Learning over Unreliable Networks Chen Yu Hanlin Tang Cédric Renggli S. Kassing Ankit Singla Dan Alistarh Ce Zhang Ji Liu OOD 208 66 0 17 Oct 2018
POLO: a POLicy-based Optimization library Arda Aytekin Martin Biel M. Johansson 82 3 0 08 Oct 2018
Anytime Stochastic Gradient Descent: A Time to Hear from all the Workers Nuwan S. Ferdinand S. Draper 154 19 0 06 Oct 2018
Sparsified SGD with Memory Sebastian U. Stich Jean-Baptiste Cordonnier Martin Jaggi 290 817 0 20 Sep 2018
Fast Variance Reduction Method with Stochastic Batch Size Xuanqing Liu Cho-Jui Hsieh 181 6 0 07 Aug 2018
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence RatesInternational Conference on Machine Learning (ICML), 2018 Kaiwen Zhou Fanhua Shang James Cheng 150 78 0 28 Jun 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification Hongyi Wang Scott Sievert Zachary B. Charles Shengchao Liu S. Wright Dimitris Papailiopoulos 237 371 0 11 Jun 2018
Federated Learning with Non-IID Data Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra FedML 456 2,923 0 02 Jun 2018
Double Quantization for Communication-Efficient Distributed Optimization Yue Yu Jiaxiang Wu Longbo Huang MQ 266 58 0 25 May 2018
Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization G. Scutari Ying Sun 233 72 0 17 May 2018
Proximal SCOPE for Distributed Sparse Learning: Better Data Partition Implies Faster Convergence RateNeural Information Processing Systems (NeurIPS), 2018 Shen-Yi Zhao Gong-Duo Zhang Ming-Wei Li Wu-Jun Li 143 8 0 15 Mar 2018
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD Sanghamitra Dutta Gauri Joshi Soumyadip Ghosh Parijat Dube P. Nagpurkar 249 203 0 03 Mar 2018
Improved asynchronous parallel optimization analysis for stochastic incremental methods Rémi Leblond Fabian Pedregosa Damien Scieur 242 75 0 11 Jan 2018
AdaBatch: Efficient Gradient Aggregation Rules for Sequential and Parallel Stochastic Gradient Methods Alexandre Défossez Francis R. Bach ODL 90 17 0 06 Nov 2017
Smooth and Sparse Optimal Transport Mathieu Blondel Vivien Seguy Antoine Rolet OT 188 188 0 17 Oct 2017