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1407.0202
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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
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Papers citing
"SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives"
50 / 878 papers shown
Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning
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22 Feb 2023
A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
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283
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17 Feb 2023
Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics
Journal of Physical Chemistry Letters (JPCL), 2023
Andreas Krämer
Aleksander E. P. Durumeric
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Yaoyi Chen
C. Clementi
Frank Noé
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14 Feb 2023
Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise
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Jiawei Zhang
Zhengyuan Zhou
234
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14 Feb 2023
DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning
International Conference on Machine Learning (ICML), 2023
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08 Feb 2023
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models
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Shangyuan Tong
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01 Feb 2023
Deep networks for system identification: a Survey
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Aleksandr Aravkin
Daniel Gedon
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Thomas B. Schon
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30 Jan 2023
Learning Large Scale Sparse Models
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Nicholas Kleene
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Optirank: classification for RNA-Seq data with optimal ranking reference genes
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Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction
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Ruqi Zhang
Shuren He
Bani Mallick
289
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09 Jan 2023
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation
Journal of machine learning research (JMLR), 2023
Xiao-Tong Yuan
P. Li
225
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09 Jan 2023
Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems
Mathematics of Operations Research (MOR), 2023
Quoc Tran-Dinh
Yang Luo
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08 Jan 2023
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization
Statistics and computing (Stat. Comput.), 2023
G. Fort
Eric Moulines
258
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02 Jan 2023
Can 5th Generation Local Training Methods Support Client Sampling? Yes!
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Michal Grudzieñ
Grigory Malinovsky
Peter Richtárik
335
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29 Dec 2022
Gradient Descent-Type Methods: Background and Simple Unified Convergence Analysis
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Marten van Dijk
161
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19 Dec 2022
Variance-Reduced Conservative Policy Iteration
International Conference on Algorithmic Learning Theory (ALT), 2022
Naman Agarwal
Brian Bullins
Karan Singh
199
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12 Dec 2022
Stochastic Optimization for Spectral Risk Measures
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Ronak R. Mehta
Vincent Roulet
Krishna Pillutla
Lang Liu
Zaïd Harchaoui
184
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10 Dec 2022
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
International Conference on Machine Learning (ICML), 2022
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Chaobing Song
Stephen J. Wright
Jelena Diakonikolas
263
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09 Dec 2022
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170
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06 Dec 2022
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Mikkel N. Schmidt
T. S. Alstrøm
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264
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05 Dec 2022
Convergence of ease-controlled Random Reshuffling gradient Algorithms under Lipschitz smoothness
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Corrado Coppola
G. Liuzzi
L. Palagi
330
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Covariance Estimators for the ROOT-SGD Algorithm in Online Learning
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143
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Closing the gap between SVRG and TD-SVRG with Gradient Splitting
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Alexander Olshevsky
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169
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29 Nov 2022
Stochastic Steffensen method
Computational optimization and applications (Comput. Optim. Appl.), 2022
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Zehua Lai
Lek-Heng Lim
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137
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28 Nov 2022
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for a Class of Nonconvex-Nonconcave Minimax Problems
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Zi Xu
Ziqi Wang
Junlin Wang
Y. Dai
270
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24 Nov 2022
Impact of Redundancy on Resilience in Distributed Optimization and Learning
International Conference of Distributed Computing and Networking (ICDCN), 2022
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Nirupam Gupta
Nitin H. Vaidya
303
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16 Nov 2022
SketchySGD: Reliable Stochastic Optimization via Randomized Curvature Estimates
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
Zachary Frangella
Pratik Rathore
Shipu Zhao
Madeleine Udell
409
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16 Nov 2022
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods
Neural Information Processing Systems (NeurIPS), 2022
Yanli Liu
Jianchao Tan
Tamer Basar
W. Yin
341
120
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15 Nov 2022
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization
Neural Information Processing Systems (NeurIPS), 2022
Ali Kavis
Stratis Skoulakis
Kimon Antonakopoulos
L. Dadi
Volkan Cevher
253
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Coresets for Vertical Federated Learning: Regularized Linear Regression and
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Lingxiao Huang
Zhize Li
Jialin Sun
Haoyu Zhao
FedML
209
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26 Oct 2022
Block-wise Primal-dual Algorithms for Large-scale Doubly Penalized ANOVA Modeling
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Penghui Fu
Z. Tan
147
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20 Oct 2022
Unsupervised visualization of image datasets using contrastive learning
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Jan Boehm
Philipp Berens
D. Kobak
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18 Oct 2022
Joint control variate for faster black-box variational inference
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Xi Wang
Tomas Geffner
Justin Domke
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291
0
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13 Oct 2022
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities
Aleksandr Beznosikov
Alexander Gasnikov
232
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Double Averaging and Gradient Projection: Convergence Guarantees for Decentralized Constrained Optimization
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Firooz Shahriari-Mehr
Ashkan Panahi
223
2
0
06 Oct 2022
A One-shot Framework for Distributed Clustered Learning in Heterogeneous Environments
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Aleksandar Armacki
Dragana Bajović
D. Jakovetić
S. Kar
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598
8
0
22 Sep 2022
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes
A. Fedorov
Eloy P. T. Geenjaar
Lei Wu
Tristan Sylvain
T. DeRamus
Margaux Luck
Maria B. Misiura
R. Devon Hjelm
Sergey Plis
Vince D. Calhoun
128
3
0
07 Sep 2022
Faster federated optimization under second-order similarity
International Conference on Learning Representations (ICLR), 2022
Ahmed Khaled
Chi Jin
FedML
288
24
0
06 Sep 2022
Versatile Single-Loop Method for Gradient Estimator: First and Second Order Optimality, and its Application to Federated Learning
Kazusato Oko
Shunta Akiyama
Tomoya Murata
Taiji Suzuki
FedML
228
0
0
01 Sep 2022
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems: A Survey
European Mathematical Society Magazine (EMS Magazine), 2022
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Boris Polyak
Eduard A. Gorbunov
D. Kovalev
Alexander Gasnikov
313
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0
29 Aug 2022
A Stochastic Variance Reduced Gradient using Barzilai-Borwein Techniques as Second Order Information
Journal of Industrial and Management Optimization (JIMO), 2022
Hardik Tankaria
N. Yamashita
166
1
0
23 Aug 2022
Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization
Journal of machine learning research (JMLR), 2022
Zhize Li
Jian Li
262
9
0
22 Aug 2022
SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters
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Zhuqing Liu
Xin Zhang
Jia-Wei Liu
235
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Long-Short History of Gradients is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning
European Symposium on Research in Computer Security (ESORICS), 2022
Ashish Gupta
Tie-Mei Luo
Mao V. Ngo
Sajal K. Das
AAML
FedML
197
25
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14 Aug 2022
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification
International Conference on Information and Knowledge Management (CIKM), 2022
Runxue Bao
Bin Gu
Heng-Chiao Huang
264
18
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11 Aug 2022
Pairwise Learning via Stagewise Training in Proximal Setting
Hilal AlQuabeh
Aliakbar Abdurahimov
138
2
0
08 Aug 2022
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity
Neural Information Processing Systems (NeurIPS), 2022
Sally Dong
Haotian Jiang
Y. Lee
Swati Padmanabhan
Guanghao Ye
221
2
0
07 Aug 2022
SGEM: stochastic gradient with energy and momentum
Hailiang Liu
Xuping Tian
129
4
0
03 Aug 2022
Stochastic Primal-Dual Three Operator Splitting Algorithm with Extension to Equivariant Regularization-by-Denoising
Junqi Tang
Matthias Joachim Ehrhardt
Carola-Bibiane Schönlieb
259
0
0
02 Aug 2022
FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Divyansh Jhunjhunwala
Pranay Sharma
Aushim Nagarkatti
Gauri Joshi
FedML
236
87
0
28 Jul 2022
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