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2206.08307
Cited By
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning
Neural Information Processing Systems (NeurIPS), 2022
16 June 2022
Anastasia Koloskova
Sebastian U. Stich
Martin Jaggi
FedML
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Papers citing
"Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning"
50 / 63 papers shown
Generative Modeling with Continuous Flows: Sample Complexity of Flow Matching
Mudit Gaur
Prashant Trivedi
Shuchin Aeron
Amrit Singh Bedi
George K. Atia
Vaneet Aggarwal
60
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0
01 Dec 2025
Stragglers Can Contribute More: Uncertainty-Aware Distillation for Asynchronous Federated Learning
Yujia Wang
Fenglong Ma
Jinghui Chen
FedML
278
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0
25 Nov 2025
PubSub-VFL: Towards Efficient Two-Party Split Learning in Heterogeneous Environments via Publisher/Subscriber Architecture
Yi Liu
Yang Liu
Leqian Zheng
Jue Hong
Junjie Shi
Qingyou Yang
Ye Wu
Cong Wang
108
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0
14 Oct 2025
Discrete State Diffusion Models: A Sample Complexity Perspective
Aadithya Srikanth
Mudit Gaur
Vaneet Aggarwal
DiffM
97
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0
12 Oct 2025
FedMuon: Federated Learning with Bias-corrected LMO-based Optimization
Yuki Takezawa
Anastasia Koloskova
Xiaowen Jiang
Sebastian U. Stich
150
0
0
30 Sep 2025
Asynchronous Policy Gradient Aggregation for Efficient Distributed Reinforcement Learning
Alexander Tyurin
Andrei Spiridonov
Varvara Rudenko
OffRL
116
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0
29 Sep 2025
Delayed Momentum Aggregation: Communication-efficient Byzantine-robust Federated Learning with Partial Participation
Kaoru Otsuka
Yuki Takezawa
Makoto Yamada
FedML
143
1
0
03 Sep 2025
Taming Latency and Bandwidth: A Theoretical Framework and Adaptive Algorithm for Communication-Constrained Training
Rongwei Lu
Jingyan Jiang
Chunyang Li
Haotian Dong
Xingguang Wei
194
1
0
23 Jul 2025
Improved Sample Complexity For Diffusion Model Training Without Empirical Risk Minimizer Access
Mudit Gaur
Prashant Trivedi
Sasidhar Kunapuli
Amrit Singh Bedi
Vaneet Aggarwal
510
0
0
23 May 2025
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-FedHT: Stepsize-Aware Hard-Threshold Gradient Compression in Federated Learning
IEEE Conference on Computer Communications (IEEE INFOCOM), 2025
Rongwei Lu
Yutong Jiang
Jinrui Zhang
Chunyang Li
Yifei Zhu
Bin Chen
Zhi Wang
FedML
340
2
0
18 May 2025
Asynchronous Decentralized SGD under Non-Convexity: A Block-Coordinate Descent Framework
Yijie Zhou
Shi Pu
161
1
0
15 May 2025
Convergence Analysis of Asynchronous Federated Learning with Gradient Compression for Non-Convex Optimization
Diying Yang
Yingwei Hou
Danyang Xiao
FedML
350
0
0
28 Apr 2025
A Tale of Two Learning Algorithms: Multiple Stream Random Walk and Asynchronous Gossip
Peyman Gholami
H. Seferoglu
147
0
0
14 Apr 2025
Orthogonal Calibration for Asynchronous Federated Learning
Jiayun Zhang
Shuheng Li
Haiyu Huang
Xiaofan Yu
Rajesh K. Gupta
Jingbo Shang
FedML
266
1
0
21 Feb 2025
Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity
Artavazd Maranjyan
Alexander Tyurin
Peter Richtárik
373
6
0
27 Jan 2025
Review of Mathematical Optimization in Federated Learning
Shusen Yang
Fangyuan Zhao
Zihao Zhou
Liang Shi
Xuebin Ren
Zongben Xu
FedML
AI4CE
327
6
0
02 Dec 2024
Boosting Asynchronous Decentralized Learning with Model Fragmentation
The Web Conference (WWW), 2024
Sayan Biswas
Anne-Marie Kermarrec
Alexis Marouani
Rafael Pires
Rishi Sharma
M. Vos
242
5
0
16 Oct 2024
MindFlayer SGD: Efficient Parallel SGD in the Presence of Heterogeneous and Random Worker Compute Times
Conference on Uncertainty in Artificial Intelligence (UAI), 2024
Artavazd Maranjyan
Omar Shaikh Omar
Peter Richtárik
270
4
0
05 Oct 2024
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
Neural Information Processing Systems (NeurIPS), 2024
Ming Xiang
Stratis Ioannidis
Edmund Yeh
Carlee Joe-Wong
Lili Su
FedML
335
9
0
26 Sep 2024
Sequential Federated Learning in Hierarchical Architecture on Non-IID Datasets
IEEE Transactions on Mobile Computing (IEEE TMC), 2024
Xingrun Yan
Shiyuan Zuo
Rongfei Fan
Han Hu
Li Shen
Puning Zhao
Yong Luo
FedML
216
0
0
19 Aug 2024
Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching
Amit Attia
Ofir Gaash
Tomer Koren
286
0
0
14 Aug 2024
Finite-Time Analysis of Asynchronous Multi-Agent TD Learning
American Control Conference (ACC), 2024
Nicolò Dal Fabbro
Arman Adibi
Aritra Mitra
George J. Pappas
217
2
0
29 Jul 2024
Ordered Momentum for Asynchronous SGD
Neural Information Processing Systems (NeurIPS), 2024
Chang-Wei Shi
Yi-Rui Yang
Wu-Jun Li
ODL
412
2
0
27 Jul 2024
FADAS: Towards Federated Adaptive Asynchronous Optimization
Yujia Wang
Shiqiang Wang
Songtao Lu
Jinghui Chen
FedML
216
12
0
25 Jul 2024
A Joint Approach to Local Updating and Gradient Compression for Efficient Asynchronous Federated Learning
Jiajun Song
Jiajun Luo
Rongwei Lu
Shuzhao Xie
Bin Chen
Zhi Wang
FedML
150
2
0
06 Jul 2024
Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods
Tim Tsz-Kit Lau
Weijian Li
Chenwei Xu
Han Liu
Mladen Kolar
304
3
0
20 Jun 2024
FedAST: Federated Asynchronous Simultaneous Training
Baris Askin
Pranay Sharma
Carlee Joe-Wong
Gauri Joshi
318
6
0
01 Jun 2024
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
Xiaolu Wang
Yuchang Sun
Hoi-To Wai
Jun Zhang
264
2
0
27 May 2024
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
Alexander Tyurin
Kaja Gruntkowska
Peter Richtárik
256
6
0
24 May 2024
Asynchronous Federated Stochastic Optimization for Heterogeneous Objectives Under Arbitrary Delays
Charikleia Iakovidou
Kibaek Kim
FedML
344
3
0
16 May 2024
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation
International Conference on Machine Learning (ICML), 2024
Haibo Yang
Pei-Yuan Qiu
Prashant Khanduri
Minghong Fang
Jia Liu
FedML
234
5
0
04 May 2024
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey
Feng Liang
Zhen Zhang
Haifeng Lu
Victor C. M. Leung
Yanyi Guo
Xiping Hu
GNN
339
24
0
09 Apr 2024
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis
Guangchen Lan
Dong-Jun Han
Abolfazl Hashemi
Vaneet Aggarwal
Christopher G. Brinton
820
22
0
09 Apr 2024
DASA: Delay-Adaptive Multi-Agent Stochastic Approximation
Nicolò Dal Fabbro
Arman Adibi
H. Vincent Poor
Sanjeev R. Kulkarni
A. Mitra
George J. Pappas
228
3
0
25 Mar 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
Arman Adibi
Nicolò Dal Fabbro
Luca Schenato
Sanjeev R. Kulkarni
H. Vincent Poor
George J. Pappas
Hamed Hassani
A. Mitra
359
9
0
19 Feb 2024
Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients
Xiaolu Wang
Zijian Li
Shi Jin
Jun Zhang
FedML
332
7
0
17 Feb 2024
Queuing dynamics of asynchronous Federated Learning
Louis Leconte
Matthieu Jonckheere
S. Samsonov
Eric Moulines
FedML
219
8
0
12 Feb 2024
CO2: Efficient Distributed Training with Full Communication-Computation Overlap
Weigao Sun
Zhen Qin
Weixuan Sun
Shidi Li
Dong Li
Xuyang Shen
Yu Qiao
Yiran Zhong
OffRL
271
15
0
29 Jan 2024
EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (IMWUT), 2024
Xiaocheng Li
Si-ren Liu
Zimu Zhou
Bin Guo
Yuan Xu
Zhiwen Yu
291
3
0
29 Jan 2024
Efficient Asynchronous Federated Learning with Sparsification and Quantization
Juncheng Jia
Ji Liu
Chendi Zhou
Hao Tian
M. Dong
Dejing Dou
FedML
305
17
0
23 Dec 2023
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-aware Model Update
AAAI Conference on Artificial Intelligence (AAAI), 2023
Ji Liu
Juncheng Jia
Tianshi Che
Chao Huo
Jiaxiang Ren
Yang Zhou
H. Dai
Dejing Dou
227
68
0
10 Dec 2023
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Mathieu Even
Anastasia Koloskova
Laurent Massoulié
FedML
328
16
0
01 Nov 2023
AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Rustem Islamov
M. Safaryan
Dan Alistarh
FedML
224
22
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Convergence Analysis of Decentralized ASGD
Mauro Dalle Lucca Tosi
Martin Theobald
259
3
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Non-ergodic linear convergence property of the delayed gradient descent under the strongly convexity and the Polyak-Łojasiewicz condition
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Hyunggwon Choi
Woocheol Choi
Jinmyoung Seok
149
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23 Aug 2023
Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Xiaoge Deng
Li Shen
Shengwei Li
Tao Sun
Dongsheng Li
Dacheng Tao
324
3
0
18 Aug 2023
Asynchronous Federated Learning with Bidirectional Quantized Communications and Buffered Aggregation
Tomàs Ortega
Hamid Jafarkhani
FedML
177
11
0
01 Aug 2023
Min-Max Optimization under Delays
American Control Conference (ACC), 2023
Arman Adibi
A. Mitra
Hamed Hassani
281
2
0
13 Jul 2023
Locally Adaptive Federated Learning
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Nicolas Loizou
Sebastian U. Stich
FedML
207
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12 Jul 2023
Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity
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Rustem Islamov
Eduard A. Gorbunov
Samuel Horváth
FedML
252
12
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29 May 2023
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