SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives

1 July 2014

Papers citing "SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives"

50 / 353 papers shown

Title
Permutation Randomization on Nonsmooth Nonconvex Optimization: A Theoretical and Experimental Study Wei Zhang Arif Hassan Zidan Afrar Jahin Wei Zhang Tianming Liu 14 0 0 16 May 2025
HOME-3: High-Order Momentum Estimator with Third-Power Gradient for Convex and Smooth Nonconvex Optimization Wei Zhang Arif Hassan Zidan Afrar Jahin Wei Zhang Tianming Liu ODL 14 0 0 16 May 2025
Personalized Federated Learning under Model Dissimilarity Constraints Samuel Erickson Mikael Johansson FedML 50 0 0 12 May 2025
Streaming Krylov-Accelerated Stochastic Gradient Descent Stephen Thomas 36 0 0 11 May 2025
Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL Jiarui Yao Yifan Hao Hanning Zhang Hanze Dong Wei Xiong Nan Jiang Tong Zhang LRM 62 0 0 05 May 2025
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression Yixuan Zhang Dongyan Yudong Chen Qiaomin Xie 40 0 0 11 Apr 2025
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning Jingruo Sun Zachary Frangella Madeleine Udell 41 0 0 28 Jan 2025
Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems Quoc Tran-Dinh Yang Luo 99 6 0 28 Jan 2025
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis Ruichen Luo Sebastian U Stich Samuel Horváth Martin Takáč 43 0 0 08 Jan 2025
Efficient Optimization Algorithms for Linear Adversarial Training Antônio H. Ribeiro Thomas B. Schon Dave Zahariah Francis Bach AAML 57 1 0 16 Oct 2024
OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement Qinglun Li Miao Zhang Mengzhu Wang Quanjun Yin Li Shen OODD FedML 26 0 0 09 Oct 2024
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation Marina Sheshukova Denis Belomestny Alain Durmus Eric Moulines Alexey Naumov S. Samsonov 46 1 0 07 Oct 2024
Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms Bin Gu Xiyuan Wei Hualin Zhang Yi Chang Heng-Chiao Huang FedML 23 0 0 03 Oct 2024
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Marcelo Hartmann Arto Klami DRL 48 0 0 03 Oct 2024
Debiasing Federated Learning with Correlated Client Participation Zhenyu Sun Ziyang Zhang Zheng Xu Gauri Joshi Pranay Sharma Ermin Wei FedML 34 0 0 02 Oct 2024
Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction Tianyu Xie Musu Yuan Minghua Deng Cheng Zhang 34 0 0 09 Sep 2024
Gradient-Free Method for Heavily Constrained Nonconvex Optimization Wanli Shi Hongchang Gao Bin Gu 21 5 0 31 Aug 2024
Ordered Momentum for Asynchronous SGD Chang-Wei Shi Yi-Rui Yang Wu-Jun Li ODL 67 0 0 27 Jul 2024
SOREL: A Stochastic Algorithm for Spectral Risks Minimization Yuze Ge Rujun Jiang 47 0 0 19 Jul 2024
PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds Zehan Zhu Yan Huang Xin Wang Jinming Xu 51 0 0 04 May 2024
Stochastic Online Optimization for Cyber-Physical and Robotic Systems Hao Ma Melanie Zeilinger Michael Muehlebach 62 0 0 08 Apr 2024
Decentralized Sum-of-Nonconvex Optimization Zhuanghua Liu K. H. Low 21 0 0 04 Feb 2024
Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems Yanjie Zhong Jiaqi Li Soumendra Lahiri 34 1 0 29 Jan 2024
Efficiently Escaping Saddle Points for Non-Convex Policy Optimization Sadegh Khorasani Saber Salehkaleybar Negar Kiyavash Niao He Matthias Grossglauser 31 1 0 15 Nov 2023
A Coefficient Makes SVRG Effective Yida Yin Zhiqiu Xu Zhiyuan Li Trevor Darrell Zhuang Liu 44 1 0 09 Nov 2023
$Computing Approximate $\ell_p$ Sensitivities$ Computing Approximate $\ell_p$ Sensitivities Swati Padmanabhan David P. Woodruff Qiuyi Zhang 58 0 0 07 Nov 2023
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates Ahmad Rammal Kaja Gruntkowska Nikita Fedin Eduard A. Gorbunov Peter Richtárik 50 5 0 15 Oct 2023
On the Parallel Complexity of Multilevel Monte Carlo in Stochastic Gradient Descent Kei Ishikawa BDL 63 0 0 03 Oct 2023
Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient Approach Leonardo F. Toso Han Wang James Anderson 37 2 0 19 Sep 2023
Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions Kwan Ho Ryan Chan Aditya Chattopadhyay B. Haeffele René Vidal 42 0 0 24 Aug 2023
GBM-based Bregman Proximal Algorithms for Constrained Learning Zhenwei Lin Qi Deng 31 1 0 21 Aug 2023
Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization M. D. Santis Jordan Frécon Francesco Rinaldi Saverio Salzo Martin Schmidt Martin Schmidt 55 0 0 21 Aug 2023
Variance-reduced accelerated methods for decentralized stochastic double-regularized nonconvex strongly-concave minimax problems Gabriel Mancino-Ball Yangyang Xu 22 8 0 14 Jul 2023
AdaSelection: Accelerating Deep Learning Training through Data Subsampling Minghe Zhang Chaosheng Dong Jinmiao Fu Tianchen Zhou Jia Liang ... Bo Liu Michinari Momma Bryan Wang Yan Gao Yi Sun 40 3 0 19 Jun 2023
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates Siqi Zhang S. Choudhury Sebastian U. Stich Nicolas Loizou FedML 28 3 0 08 Jun 2023
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation Davoud Ataee Tarzanagh Mingchen Li Pranay Sharma Samet Oymak 36 0 0 02 Jun 2023
Differentiable Clustering with Perturbed Spanning Forests Lawrence Stewart Francis R. Bach Felipe Llinares-López Quentin Berthet 34 8 0 25 May 2023
Stochastic Ratios Tracking Algorithm for Large Scale Machine Learning Problems Shigeng Sun Yuchen Xie 18 3 0 17 May 2023
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features Aleksandr Beznosikov David Dobre Gauthier Gidel 30 5 0 23 Apr 2023
Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective Adam N. Elmachtoub Henry Lam Haofeng Zhang Yunfan Zhao 41 6 0 13 Apr 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 35 20 0 14 Feb 2023
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise Zijian Liu Jiawei Zhang Zhengyuan Zhou 39 12 0 14 Feb 2023
Optirank: classification for RNA-Seq data with optimal ranking reference genes Paola Malsot F. Martins D. Trono G. Obozinski 15 0 0 11 Jan 2023
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction Bowen Lei Dongkuan Xu Ruqi Zhang Shuren He Bani Mallick 44 6 0 09 Jan 2023
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation Xiao-Tong Yuan P. Li 41 2 0 09 Jan 2023
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization G. Fort Eric Moulines 46 6 0 02 Jan 2023
Gradient Descent-Type Methods: Background and Simple Unified Convergence Analysis Quoc Tran-Dinh Marten van Dijk 34 0 0 19 Dec 2022
Variance-Reduced Conservative Policy Iteration Naman Agarwal Brian Bullins Karan Singh 32 3 0 12 Dec 2022
Stochastic Optimization for Spectral Risk Measures Ronak R. Mehta Vincent Roulet Krishna Pillutla Lang Liu Zaïd Harchaoui 42 6 0 10 Dec 2022
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization Xu Cai Chaobing Song Stephen J. Wright Jelena Diakonikolas 38 14 0 09 Dec 2022