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2106.07820
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On Large-Cohort Training for Federated Learning
Neural Information Processing Systems (NeurIPS), 2021
15 June 2021
Zachary B. Charles
Zachary Garrett
Zhouyuan Huo
Sergei Shmulyian
Virginia Smith
FedML
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Papers citing
"On Large-Cohort Training for Federated Learning"
17 / 67 papers shown
QUIC-FL: Quick Unbiased Compression for Federated Learning
Ran Ben-Basat
S. Vargaftik
Amit Portnoy
Gil Einziger
Y. Ben-Itzhak
Michael Mitzenmacher
FedML
338
14
0
26 May 2022
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering
International Conference on Machine Learning (ICML), 2022
Ekdeep Singh Lubana
Chi Ian Tang
F. Kawsar
Robert P. Dick
Akhil Mathur
FedML
214
64
0
23 May 2022
Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints
IEEE Journal on Selected Topics in Signal Processing (IEEE JSTSP), 2022
Mónica Ribero
H. Vikalo
G. Veciana
FedML
261
58
0
13 May 2022
FLAME: Federated Learning Across Multi-device Environments
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (IMWUT), 2022
Hyunsung Cho
Akhil Mathur
F. Kawsar
200
27
0
17 Feb 2022
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams
Neural Information Processing Systems (NeurIPS), 2022
S. Denisov
H. B. McMahan
J. Rush
Adam D. Smith
Abhradeep Thakurta
FedML
446
79
0
16 Feb 2022
Server-Side Stepsizes and Sampling Without Replacement Provably Help in Federated Optimization
Grigory Malinovsky
Konstantin Mishchenko
Peter Richtárik
FedML
145
29
0
26 Jan 2022
Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory
Nicole Mitchell
Johannes Ballé
Zachary B. Charles
Jakub Konecný
FedML
289
25
0
07 Jan 2022
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning
Ayush Chopra
Surya Kant Sahu
Abhishek Singh
Abhinav Java
Praneeth Vepakomma
Vivek Sharma
Ramesh Raskar
178
30
0
02 Dec 2021
Papaya: Practical, Private, and Scalable Federated Learning
Dzmitry Huba
John Nguyen
Kshitiz Malik
Ruiyu Zhu
Michael G. Rabbat
...
H. Srinivas
Kaikai Wang
Anthony Shoumikhin
Jesik Min
Mani Malek
FedML
333
155
0
08 Nov 2021
Sustainable AI: Environmental Implications, Challenges and Opportunities
Conference on Machine Learning and Systems (MLSys), 2021
Carole-Jean Wu
Ramya Raghavendra
Udit Gupta
Bilge Acun
Newsha Ardalani
...
Maximilian Balandat
Joe Spisak
R. Jain
Michael G. Rabbat
K. Hazelwood
403
539
0
30 Oct 2021
Boosting Resource-Constrained Federated Learning Systems with Guessed Updates
IEEE Transactions on Parallel and Distributed Systems (TPDS), 2021
Mohamed Yassine Boukhari
Akash Dhasade
Anne-Marie Kermarrec
Rafael Pires
Othmane Safsafi
Rishi Sharma
FedML
242
0
0
21 Oct 2021
Anarchic Federated Learning
International Conference on Machine Learning (ICML), 2021
Haibo Yang
Xin Zhang
Prashant Khanduri
Jia Liu
FedML
205
62
0
23 Aug 2021
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning
Charlie Hou
K. K. Thekumparampil
Giulia Fanti
Sewoong Oh
FedML
273
15
0
16 Aug 2021
A Field Guide to Federated Optimization
Jianyu Wang
Zachary B. Charles
Zheng Xu
Gauri Joshi
H. B. McMahan
...
Mi Zhang
Tong Zhang
Chunxiang Zheng
Chen Zhu
Wennan Zhu
FedML
506
461
0
14 Jul 2021
On the Convergence of Differentially Private Federated Learning on Non-Lipschitz Objectives, and with Normalized Client Updates
Rudrajit Das
Abolfazl Hashemi
Sujay Sanghavi
Inderjit S. Dhillon
FedML
158
4
0
13 Jun 2021
Federated Learning with Buffered Asynchronous Aggregation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
John Nguyen
Kshitiz Malik
Hongyuan Zhan
Ashkan Yousefpour
Michael G. Rabbat
Mani Malek
Dzmitry Huba
FedML
380
401
0
11 Jun 2021
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
Sai Praneeth Karimireddy
Martin Jaggi
Satyen Kale
M. Mohri
Sashank J. Reddi
Sebastian U. Stich
A. Suresh
FedML
548
236
0
08 Aug 2020
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