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SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly
  Convex Composite Objectives
v1v2v3 (latest)

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

Neural Information Processing Systems (NeurIPS), 2014
1 July 2014
Aaron Defazio
Francis R. Bach
Damien Scieur
    ODL
ArXiv (abs)PDFHTML

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

50 / 878 papers shown
Accelerated Distributional Temporal Difference Learning with Linear Function Approximation
Accelerated Distributional Temporal Difference Learning with Linear Function Approximation
Kaicheng Jin
Yang Peng
Jiansheng Yang
Zhihua Zhang
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0
0
16 Nov 2025
Sampling and Loss Weights in Multi-Domain Training
Sampling and Loss Weights in Multi-Domain Training
Mahdi Salmani
Pratik Worah
Meisam Razaviyayn
Vahab Mirrokni
NoLa
298
0
0
10 Nov 2025
Structured Matrix Scaling for Multi-Class Calibration
Structured Matrix Scaling for Multi-Class Calibration
Eugene Berta
David Holzmüller
Michael I. Jordan
Francis Bach
128
1
0
05 Nov 2025
Convergence Analysis of SGD under Expected Smoothness
Convergence Analysis of SGD under Expected Smoothness
Yuta Kawamoto
Hideaki Iiduka
144
0
0
23 Oct 2025
On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
Shaocong Ma
Heng Huang
135
2
0
22 Oct 2025
MARS-M: When Variance Reduction Meets Matrices
MARS-M: When Variance Reduction Meets Matrices
Yifeng Liu
Angela Yuan
Q. Gu
222
1
0
20 Oct 2025
Personalized Collaborative Learning with Affinity-Based Variance Reduction
Personalized Collaborative Learning with Affinity-Based Variance Reduction
Chenyu Zhang
Navid Azizan
96
0
0
17 Oct 2025
The Cognitive Bandwidth Bottleneck: Shifting Long-Horizon Agent from Planning with Actions to Planning with Schemas
The Cognitive Bandwidth Bottleneck: Shifting Long-Horizon Agent from Planning with Actions to Planning with Schemas
Baixuan Xu
Tianshi Zheng
Zhaowei Wang
Hong Ting Tsang
Weiqi Wang
Tianqing Fang
Yangqiu Song
148
0
0
08 Oct 2025
H+: An Efficient Similarity-Aware Aggregation for Byzantine Resilient Federated Learning
H+: An Efficient Similarity-Aware Aggregation for Byzantine Resilient Federated Learning
Shiyuan Zuo
Rongfei Fan
Cheng Zhan
Jie Xu
P. Zhao
Han Hu
AAML
111
0
0
29 Sep 2025
SPRINT: Stochastic Performative Prediction With Variance Reduction
SPRINT: Stochastic Performative Prediction With Variance Reduction
Tian Xie
Ding Zhu
Jia Liu
Mahdi Khalili
X. Zhang
186
1
0
22 Sep 2025
Do Natural Language Descriptions of Model Activations Convey Privileged Information?
Do Natural Language Descriptions of Model Activations Convey Privileged Information?
Millicent Li
Alberto Mario Ceballos Arroyo
Giordano Rogers
Naomi Saphra
Byron C. Wallace
173
2
0
16 Sep 2025
Shuffling Heuristic in Variational Inequalities: Establishing New Convergence Guarantees
Shuffling Heuristic in Variational Inequalities: Establishing New Convergence Guarantees
Daniil Medyakov
Gleb Molodtsov
Grigoriy Evseev
Egor Petrov
Aleksandr Beznosikov
331
3
0
04 Sep 2025
A Hybrid Stochastic Gradient Tracking Method for Distributed Online Optimization Over Time-Varying Directed Networks
A Hybrid Stochastic Gradient Tracking Method for Distributed Online Optimization Over Time-Varying Directed Networks
Xinli Shi
Xingxing Yuan
Longkang Zhu
G. Wen
84
0
0
28 Aug 2025
Stochastic Gradient Descent with Strategic Querying
Stochastic Gradient Descent with Strategic Querying
Nanfei Jiang
Hoi-To Wai
M. Alizadeh
109
0
0
23 Aug 2025
Jointly Computation- and Communication-Efficient Distributed Learning
Jointly Computation- and Communication-Efficient Distributed Learning
Xiaoxing Ren
Nicola Bastianello
Karl H. Johansson
Thomas Parisini
FedML
288
0
0
21 Aug 2025
Detecting COPD Through Speech Analysis: A Dataset of Danish Speech and Machine Learning Approach
Detecting COPD Through Speech Analysis: A Dataset of Danish Speech and Machine Learning Approach
Cuno Sankey-Olsen
Rasmus Hvass Olesen
Tobias Oliver Eberhard
Andreas Triantafyllopoulos
B. Schuller
Ilhan Aslan
92
0
0
04 Aug 2025
EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes
EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes
Adam Block
Cyril Zhang
158
1
0
31 Jul 2025
Adjusted Shuffling SARAH: Advancing Complexity Analysis via Dynamic Gradient Weighting
Adjusted Shuffling SARAH: Advancing Complexity Analysis via Dynamic Gradient Weighting
Duc Toan Nguyen
Trang H. Tran
Lam M. Nguyen
133
0
0
14 Jun 2025
NDCG-Consistent Softmax Approximation with Accelerated Convergence
Yuanhao Pu
Defu Lian
Xiaolong Chen
Xu Huang
Jin Chen
Enhong Chen
161
0
0
11 Jun 2025
Leveraging Coordinate Momentum in SignSGD and Muon: Memory-Optimized Zero-Order
Leveraging Coordinate Momentum in SignSGD and Muon: Memory-Optimized Zero-Order
Egor Petrov
Grigoriy Evseev
Aleksey Antonov
Andrey Veprikov
Nikolay Bushkov
Nikolay Bushkov
Stanislav Moiseev
403
2
0
04 Jun 2025
HOME-3: High-Order Momentum Estimator with Third-Power Gradient for Convex and Smooth Nonconvex Optimization
HOME-3: High-Order Momentum Estimator with Third-Power Gradient for Convex and Smooth Nonconvex Optimization
Wei Zhang
Arif Hassan Zidan
Arif Hassan Zidan
Wei Zhang
Tianming Liu
ODL
259
0
0
16 May 2025
Permutation Randomization on Nonsmooth Nonconvex Optimization: A Theoretical and Experimental Study
Permutation Randomization on Nonsmooth Nonconvex Optimization: A Theoretical and Experimental Study
Wei Zhang
Arif Hassan Zidan
Arif Hassan Zidan
Wei Zhang
Tianming Liu
189
0
0
16 May 2025
Personalized Federated Learning under Model Dissimilarity Constraints
Personalized Federated Learning under Model Dissimilarity Constraints
Samuel Erickson
Mikael Johansson
FedML
665
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0
12 May 2025
Streaming Krylov-Accelerated Stochastic Gradient Descent
Streaming Krylov-Accelerated Stochastic Gradient Descent
Stephen Thomas
124
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0
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Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL
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
385
10
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A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile RegressionMeasurement and Modeling of Computer Systems (SIGMETRICS), 2025
Yixuan Zhang
Dongyan
Yudong Chen
Qiaomin Xie
260
1
0
11 Apr 2025
Node Embeddings via Neighbor Embeddings
Node Embeddings via Neighbor Embeddings
Jan Niklas Böhm
Marius Keute
Alica Guzmán
Sebastian Damrich
Andrew Draganov
D. Kobak
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353
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A Flexible Fairness Framework with Surrogate Loss Reweighting for Addressing Sociodemographic Disparities
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Wen Xu
Elham Dolatabadi
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258
1
0
21 Mar 2025
Convergence Analysis of alpha-SVRG under Strong Convexity
Convergence Analysis of alpha-SVRG under Strong ConvexityIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025
Sean Xiao
Sangwoo Park
Stefan Vlaski
229
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0
16 Mar 2025
FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration
Xue Feng
M. Paul Laiu
Thomas Strohmer
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181
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Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling
Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling
Daniil Medyakov
Gleb Molodtsov
S. Chezhegov
Alexey Rebrikov
Aleksandr Beznosikov
416
1
0
20 Feb 2025
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning
Jingruo Sun
Zachary Frangella
Madeleine Udell
214
2
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28 Jan 2025
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing AnalysisInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Ruichen Luo
Sebastian U Stich
Samuel Horváth
Martin Takáč
522
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08 Jan 2025
Accelerated Methods with Compressed Communications for Distributed
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Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data SimilarityAAAI Conference on Artificial Intelligence (AAAI), 2024
Dmitry Bylinkin
Aleksandr Beznosikov
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Analysis of regularized federated learning
Analysis of regularized federated learning
Langming Liu
Dingxuan Zhou
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134
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03 Nov 2024
Analysis of ELSA COVID-19 Substudy response rate using machine learning
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Analysis of ELSA COVID-19 Substudy response rate using machine learning algorithms
Marjan Qazvini
204
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Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration
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Efficient Optimization Algorithms for Linear Adversarial Training
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Boosting the Performance of Decentralized Federated Learning via
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Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation
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Obtaining Lower Query Complexities through Lightweight Zeroth-Order
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On the SAGA algorithm with decreasing step
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Debiasing Federated Learning with Correlated Client Participation
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297
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Decentralized Federated Learning with Gradient Tracking over
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Accelerated Stochastic ExtraGradient: Mixing Hessian and Gradient
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Gradient-Free Method for Heavily Constrained Nonconvex Optimization
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Zeroth-Order Stochastic Mirror Descent Algorithms for Minimax Excess
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