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Minimizing Finite Sums with the Stochastic Average Gradient

10 September 2013

Mark Schmidt

Nicolas Le Roux

Francis R. Bach

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Papers citing "Minimizing Finite Sums with the Stochastic Average Gradient"

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Title
Unified analysis of SGD-type methods Eduard A. Gorbunov 74 2 0 29 Mar 2023
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization Cheuk Yin Lin Chaobing Song Jelena Diakonikolas 44 6 0 28 Mar 2023
Convergence of variational Monte Carlo simulation and scale-invariant pre-training Nilin Abrahamsen Zhiyan Ding Gil Goldshlager Lin Lin DRL 74 2 0 21 Mar 2023
PA&DA: Jointly Sampling PAth and DAta for Consistent NAS Shunong Lu Yu Hu Longxing Yang Zihao Sun Jilin Mei Jianchao Tan Chengru Song 47 9 0 28 Feb 2023
Stochastic Gradient Descent under Markovian Sampling Schemes Mathieu Even 67 29 0 28 Feb 2023
A Log-linear Gradient Descent Algorithm for Unbalanced Binary Classification using the All Pairs Squared Hinge Loss Kyle R. Rust T. Hocking 34 1 0 21 Feb 2023
Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics Andreas Krämer Aleksander E. P. Durumeric N. Charron Yaoyi Chen C. Clementi Frank Noé AI4CE 70 22 0 14 Feb 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning Youssef Allouah R. Guerraoui Nirupam Gupta Rafael Pinot John Stephan FedML 70 27 0 09 Feb 2023
Coordinating Distributed Example Orders for Provably Accelerated Training A. Feder Cooper Wentao Guo Khiem Pham Tiancheng Yuan Charlie F. Ruan Yucheng Lu Chris De Sa 153 7 0 02 Feb 2023
Gradient Descent-Type Methods: Background and Simple Unified Convergence Analysis Quoc Tran-Dinh Marten van Dijk 53 0 0 19 Dec 2022
Variance-Reduced Conservative Policy Iteration Naman Agarwal Brian Bullins Karan Singh 56 3 0 12 Dec 2022
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization Xu Cai Chaobing Song Stephen J. Wright Jelena Diakonikolas 80 14 0 09 Dec 2022
Convergence of ease-controlled Random Reshuffling gradient Algorithms under Lipschitz smoothness R. Seccia Corrado Coppola G. Liuzzi L. Palagi 66 2 0 04 Dec 2022
Closing the gap between SVRG and TD-SVRG with Gradient Splitting Arsenii Mustafin Alexander Olshevsky I. Paschalidis 31 1 0 29 Nov 2022
Preferential Subsampling for Stochastic Gradient Langevin Dynamics Srshti Putcha Christopher Nemeth Paul Fearnhead 50 0 0 28 Oct 2022
GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity Artavazd Maranjyan M. Safaryan Peter Richtárik 96 13 0 28 Oct 2022
A Survey of Dataset Refinement for Problems in Computer Vision Datasets Zhijing Wan Zhixiang Wang CheukTing Chung Zheng Wang 87 10 0 21 Oct 2022
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities Aleksandr Beznosikov Alexander Gasnikov 83 2 0 12 Oct 2022
A Stochastic Variance Reduced Gradient using Barzilai-Borwein Techniques as Second Order Information Hardik Tankaria N. Yamashita 45 1 0 23 Aug 2022
Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization Zhize Li Jian Li 101 6 0 22 Aug 2022
SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters Zhuqing Liu Xin Zhang Jia-Wei Liu 94 1 0 17 Aug 2022
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity Sally Dong Haotian Jiang Y. Lee Swati Padmanabhan Guanghao Ye 62 2 0 07 Aug 2022
FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning Divyansh Jhunjhunwala Pranay Sharma Aushim Nagarkatti Gauri Joshi FedML 100 67 0 28 Jul 2022
SPIRAL: A superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization Pourya Behmandpoor P. Latafat Andreas Themelis Marc Moonen Panagiotis Patrinos 52 2 0 17 Jul 2022
Benchopt: Reproducible, efficient and collaborative optimization benchmarks Thomas Moreau Mathurin Massias Alexandre Gramfort Pierre Ablin Pierre-Antoine Bannier Benjamin Charlier ... Binh Duc Nguyen A. Rakotomamonjy Zaccharie Ramzi Joseph Salmon Samuel Vaiter 124 36 0 27 Jun 2022
Gradient Descent for Low-Rank Functions Romain Cosson Ali Jadbabaie A. Makur Amirhossein Reisizadeh Devavrat Shah 88 3 0 16 Jun 2022
Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems Yunwen Lei 37 19 0 14 Jun 2022
Federated Adversarial Training with Transformers Ahmed Aldahdooh W. Hamidouche Olivier Déforges FedML ViT 83 2 0 05 Jun 2022
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top Eduard A. Gorbunov Samuel Horváth Peter Richtárik Gauthier Gidel AAML 38 0 0 01 Jun 2022
A principled framework for the design and analysis of token algorithms Hadrien Hendrikx FedML 79 16 0 30 May 2022
GraB: Finding Provably Better Data Permutations than Random Reshuffling Yucheng Lu Wentao Guo Christopher De Sa FedML 76 17 0 22 May 2022
On the efficiency of Stochastic Quasi-Newton Methods for Deep Learning M. Yousefi Angeles Martinez ODL 43 1 0 18 May 2022
Can We Do Better Than Random Start? The Power of Data Outsourcing Yi Chen Jing-rong Dong Xin T. Tong 33 0 0 17 May 2022
Neighbor-Based Optimized Logistic Regression Machine Learning Model For Electric Vehicle Occupancy Detection S. Shaw Keaton Chia J. Kleissl 20 1 0 28 Apr 2022
cu_FastTucker: A Faster and Stabler Stochastic Optimization for Parallel Sparse Tucker Decomposition on Multi-GPUs Zixuan Li 135 2 0 14 Apr 2022
Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions Xu Cai Chaobing Song Cristóbal Guzmán Jelena Diakonikolas 114 11 0 17 Mar 2022
Accelerated SGD for Non-Strongly-Convex Least Squares Aditya Varre Nicolas Flammarion 68 7 0 03 Mar 2022
Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization Gideon Dresdner Maria-Luiza Vladarean Olivier Fercoq Francesco Locatello Volkan Cevher A. Yurtsever 41 1 0 26 Feb 2022
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods Yujia Jin Aaron Sidford Kevin Tian 81 31 0 09 Feb 2022
Distributed Learning With Sparsified Gradient Differences Yicheng Chen Rick S. Blum Martin Takáč Brian M. Sadler 77 15 0 05 Feb 2022
Decentralized Stochastic Variance Reduced Extragradient Method Luo Luo Haishan Ye 110 7 0 01 Feb 2022
L-SVRG and L-Katyusha with Adaptive Sampling Boxin Zhao Boxiang Lyu Mladen Kolar 75 3 0 31 Jan 2022
Adaptive Accelerated (Extra-)Gradient Methods with Variance Reduction Zijian Liu Ta Duy Nguyen Alina Ene Huy Le Nguyen 63 6 0 28 Jan 2022
Optimal variance-reduced stochastic approximation in Banach spaces Wenlong Mou K. Khamaru Martin J. Wainwright Peter L. Bartlett Michael I. Jordan 81 9 0 21 Jan 2022
Quasi-Newton acceleration of EM and MM algorithms via Broyden $'$ s method Medha Agarwal Jason Xu 23 1 0 15 Jan 2022
Federated Optimization of Smooth Loss Functions Ali Jadbabaie A. Makur Devavrat Shah FedML 425 7 0 06 Jan 2022
Accelerated and instance-optimal policy evaluation with linear function approximation Tianjiao Li Guanghui Lan A. Pananjady OffRL 91 13 0 24 Dec 2021
FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation Xingyu Li Zhe Qu Bo Tang Zhuo Lu FedML 109 28 0 22 Dec 2021
LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization Huiming Chen Huandong Wang Quanming Yao Yong Li Depeng Jin Qiang Yang FedML 65 5 0 15 Dec 2021
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With Supplement Parikshit Ram Kaushik Sinha FedML 67 1 0 14 Dec 2021