ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1611.00429
  4. Cited By
Distributed Mean Estimation with Limited Communication
v1v2v3 (latest)

Distributed Mean Estimation with Limited Communication

2 November 2016
A. Suresh
Felix X. Yu
Sanjiv Kumar
H. B. McMahan
    FedML
ArXiv (abs)PDFHTML

Papers citing "Distributed Mean Estimation with Limited Communication"

50 / 196 papers shown
Unbiased Single-scale and Multi-scale Quantizers for Distributed
  Optimization
Unbiased Single-scale and Multi-scale Quantizers for Distributed Optimization
S. Vineeth
MQ
129
0
0
26 Sep 2021
Critical Learning Periods in Federated Learning
Critical Learning Periods in Federated Learning
Gang Yan
Hao Wang
Jian Li
FedML
199
13
0
12 Sep 2021
Fundamental limits of over-the-air optimization: Are analog schemes
  optimal?
Fundamental limits of over-the-air optimization: Are analog schemes optimal?
Shubham K. Jha
Prathamesh Mayekar
Himanshu Tyagi
171
10
0
11 Sep 2021
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for
  Federated Learning
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning
S. Vargaftik
Ran Ben-Basat
Amit Portnoy
Gal Mendelson
Y. Ben-Itzhak
Michael Mitzenmacher
FedML
294
56
0
19 Aug 2021
FedJAX: Federated learning simulation with JAX
FedJAX: Federated learning simulation with JAX
Jae Hun Ro
A. Suresh
Ke Wu
FedML
246
55
0
04 Aug 2021
DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient
  Distributed Learning
DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient Distributed LearningIEEE International Conference on Mobile Adhoc and Sensor Systems (MASS), 2021
Guangfeng Yan
Shao-Lun Huang
Tian-Shing Lan
Linqi Song
MQ
122
7
0
30 Jul 2021
A Field Guide to Federated Optimization
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
518
463
0
14 Jul 2021
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max
  Optimization Problems
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max Optimization ProblemsSignal Processing (Signal Process.), 2021
Babak Barazandeh
Tianjian Huang
George Michailidis
230
13
0
10 Jun 2021
Private Counting from Anonymous Messages: Near-Optimal Accuracy with
  Vanishing Communication Overhead
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication OverheadInternational Conference on Machine Learning (ICML), 2020
Badih Ghazi
Ravi Kumar
Pasin Manurangsi
Rasmus Pagh
FedML
216
55
0
08 Jun 2021
DRIVE: One-bit Distributed Mean Estimation
DRIVE: One-bit Distributed Mean EstimationNeural Information Processing Systems (NeurIPS), 2021
S. Vargaftik
Ran Ben-Basat
Amit Portnoy
Gal Mendelson
Y. Ben-Itzhak
Michael Mitzenmacher
OODFedML
654
58
0
18 May 2021
Slashing Communication Traffic in Federated Learning by Transmitting
  Clustered Model Updates
Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model UpdatesIEEE Journal on Selected Areas in Communications (JSAC), 2021
Laizhong Cui
Xiaoxin Su
Yipeng Zhou
Yi Pan
FedML
162
45
0
10 May 2021
Communication-Efficient Agnostic Federated Averaging
Communication-Efficient Agnostic Federated AveragingInterspeech (Interspeech), 2021
Jae Hun Ro
Mingqing Chen
Rajiv Mathews
M. Mohri
A. Suresh
FedML
274
17
0
06 Apr 2021
Efficient Randomized Subspace Embeddings for Distributed Optimization
  under a Communication Budget
Efficient Randomized Subspace Embeddings for Distributed Optimization under a Communication BudgetIEEE Journal on Selected Areas in Information Theory (JSAIT), 2021
R. Saha
Mert Pilanci
Andrea J. Goldsmith
233
6
0
13 Mar 2021
Pufferfish: Communication-efficient Models At No Extra Cost
Pufferfish: Communication-efficient Models At No Extra CostConference on Machine Learning and Systems (MLSys), 2021
Hongyi Wang
Saurabh Agarwal
Dimitris Papailiopoulos
146
67
0
05 Mar 2021
Moshpit SGD: Communication-Efficient Decentralized Training on
  Heterogeneous Unreliable Devices
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable DevicesNeural Information Processing Systems (NeurIPS), 2021
Max Ryabinin
Eduard A. Gorbunov
Vsevolod Plokhotnyuk
Gennady Pekhimenko
357
46
0
04 Mar 2021
On the Utility of Gradient Compression in Distributed Training Systems
On the Utility of Gradient Compression in Distributed Training SystemsConference on Machine Learning and Systems (MLSys), 2021
Saurabh Agarwal
Hongyi Wang
Shivaram Venkataraman
Dimitris Papailiopoulos
317
55
0
28 Feb 2021
Lossless Compression of Efficient Private Local Randomizers
Lossless Compression of Efficient Private Local RandomizersInternational Conference on Machine Learning (ICML), 2021
Vitaly Feldman
Kunal Talwar
215
43
0
24 Feb 2021
Learning with User-Level Privacy
Learning with User-Level PrivacyNeural Information Processing Systems (NeurIPS), 2021
Daniel Levy
Ziteng Sun
Kareem Amin
Satyen Kale
Alex Kulesza
M. Mohri
A. Suresh
FedML
321
102
0
23 Feb 2021
MARINA: Faster Non-Convex Distributed Learning with Compression
MARINA: Faster Non-Convex Distributed Learning with CompressionInternational Conference on Machine Learning (ICML), 2021
Eduard A. Gorbunov
Konstantin Burlachenko
Zhize Li
Peter Richtárik
323
123
0
15 Feb 2021
Distributed Online Learning for Joint Regret with Communication
  Constraints
Distributed Online Learning for Joint Regret with Communication ConstraintsInternational Conference on Algorithmic Learning Theory (ALT), 2021
Dirk van der Hoeven
Hédi Hadiji
T. Erven
204
6
0
15 Feb 2021
Communication-Efficient Distributed Optimization with Quantized
  Preconditioners
Communication-Efficient Distributed Optimization with Quantized PreconditionersInternational Conference on Machine Learning (ICML), 2021
Foivos Alimisis
Peter Davies
Dan Alistarh
225
17
0
14 Feb 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with
  Secure Aggregation
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure AggregationInternational Conference on Machine Learning (ICML), 2021
Peter Kairouz
Ziyu Liu
Thomas Steinke
FedML
448
279
0
12 Feb 2021
Adaptive Quantization of Model Updates for Communication-Efficient
  Federated Learning
Adaptive Quantization of Model Updates for Communication-Efficient Federated LearningIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021
Divyansh Jhunjhunwala
Advait Gadhikar
Gauri Joshi
Yonina C. Eldar
FedMLMQ
219
126
0
08 Feb 2021
Applications of Federated Learning in Smart Cities: Recent Advances,
  Taxonomy, and Open Challenges
Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges
Zhaohua Zheng
Yize Zhou
Yilong Sun
Zhang Wang
Boyi Liu
Keqiu Li
210
138
0
02 Feb 2021
CosSGD: Communication-Efficient Federated Learning with a Simple
  Cosine-Based Quantization
CosSGD: Communication-Efficient Federated Learning with a Simple Cosine-Based Quantization
Yang He
Hui-Po Wang
M. Zenk
Mario Fritz
FedMLMQ
227
10
0
15 Dec 2020
Quantizing data for distributed learning
Quantizing data for distributed learningIEEE Journal on Selected Areas in Information Theory (JSAIT), 2020
Osama A. Hanna
Yahya H. Ezzeldin
Christina Fragouli
Suhas Diggavi
FedML
368
24
0
14 Dec 2020
Faster Non-Convex Federated Learning via Global and Local Momentum
Faster Non-Convex Federated Learning via Global and Local Momentum
Rudrajit Das
Anish Acharya
Abolfazl Hashemi
Sujay Sanghavi
Inderjit S. Dhillon
Ufuk Topcu
FedML
509
96
0
07 Dec 2020
Wyner-Ziv Estimators for Distributed Mean Estimation with Side
  Information and Optimization
Wyner-Ziv Estimators for Distributed Mean Estimation with Side Information and OptimizationIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Prathamesh Mayekar
Shubham K. Jha
A. Suresh
Himanshu Tyagi
FedML
275
2
0
24 Nov 2020
FDNAS: Improving Data Privacy and Model Diversity in AutoML
FDNAS: Improving Data Privacy and Model Diversity in AutoML
Chunhui Zhang
Yongyuan Liang
Xiaoming Yuan
Lei Cheng
FedML
83
1
0
06 Nov 2020
A Linearly Convergent Algorithm for Decentralized Optimization: Sending
  Less Bits for Free!
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
D. Kovalev
Anastasia Koloskova
Martin Jaggi
Peter Richtárik
Sebastian U. Stich
214
80
0
03 Nov 2020
Towards Tight Communication Lower Bounds for Distributed Optimisation
Towards Tight Communication Lower Bounds for Distributed OptimisationNeural Information Processing Systems (NeurIPS), 2020
Dan Alistarh
Janne H. Korhonen
FedML
182
10
0
16 Oct 2020
Oort: Efficient Federated Learning via Guided Participant Selection
Oort: Efficient Federated Learning via Guided Participant Selection
Fan Lai
Xiangfeng Zhu
H. Madhyastha
Mosharaf Chowdhury
FedMLOODD
488
312
0
12 Oct 2020
Fairness-aware Agnostic Federated Learning
Fairness-aware Agnostic Federated LearningSDM (SDM), 2020
Wei Du
Depeng Xu
Xintao Wu
Hanghang Tong
FedML
226
151
0
10 Oct 2020
Optimal Gradient Compression for Distributed and Federated Learning
Optimal Gradient Compression for Distributed and Federated Learning
Alyazeed Albasyoni
M. Safaryan
Laurent Condat
Peter Richtárik
FedML
148
71
0
07 Oct 2020
Artificial Intelligence for UAV-enabled Wireless Networks: A Survey
Artificial Intelligence for UAV-enabled Wireless Networks: A SurveyIEEE Open Journal of the Communications Society (OJ-COMSOC), 2020
Mohamed-Amine Lahmeri
Mustafa A. Kishk
Mohamed-Slim Alouini
280
122
0
24 Sep 2020
Communication Efficient Distributed Learning with Censored, Quantized,
  and Generalized Group ADMM
Communication Efficient Distributed Learning with Censored, Quantized, and Generalized Group ADMM
Chaouki Ben Issaid
Anis Elgabli
Jihong Park
M. Bennis
Mérouane Debbah
FedML
211
13
0
14 Sep 2020
FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature
  Engineering Framework
FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework
Pei Fang
Zhendong Cai
Hui Chen
Qingjiang Shi
125
6
0
05 Sep 2020
ESMFL: Efficient and Secure Models for Federated Learning
ESMFL: Efficient and Secure Models for Federated Learning
Sheng Lin
Chenghong Wang
Hongjia Li
Jieren Deng
Yanzhi Wang
Caiwen Ding
FedML
134
6
0
03 Sep 2020
Shuffled Model of Federated Learning: Privacy, Communication and
  Accuracy Trade-offs
Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs
Antonious M. Girgis
Deepesh Data
Suhas Diggavi
Peter Kairouz
A. Suresh
FedML
188
26
0
17 Aug 2020
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
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
552
237
0
08 Aug 2020
Communication-Efficient Federated Learning via Optimal Client Sampling
Communication-Efficient Federated Learning via Optimal Client Sampling
Mónica Ribero
H. Vikalo
FedML
198
104
0
30 Jul 2020
Breaking the Communication-Privacy-Accuracy Trilemma
Breaking the Communication-Privacy-Accuracy Trilemma
Wei-Ning Chen
Peter Kairouz
Ayfer Özgür
462
130
0
22 Jul 2020
Federated Learning with Compression: Unified Analysis and Sharp
  Guarantees
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour
Mohammad Mahdi Kamani
Aryan Mokhtari
M. Mahdavi
FedML
455
316
0
02 Jul 2020
D2P-Fed: Differentially Private Federated Learning With Efficient
  Communication
D2P-Fed: Differentially Private Federated Learning With Efficient Communication
Lun Wang
R. Jia
Dawn Song
FedML
207
0
0
22 Jun 2020
Distributed Newton Can Communicate Less and Resist Byzantine Workers
Distributed Newton Can Communicate Less and Resist Byzantine Workers
Avishek Ghosh
R. Maity
A. Mazumdar
FedML
169
37
0
15 Jun 2020
Characterizing Impacts of Heterogeneity in Federated Learning upon
  Large-Scale Smartphone Data
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data
Chengxu Yang
Qipeng Wang
Mengwei Xu
Shangguang Wang
Kaigui Bian
Yunxin Liu
Xuanzhe Liu
177
24
0
12 Jun 2020
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data
Deepesh Data
Suhas Diggavi
FedML
157
45
0
16 May 2020
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized
  Optimization
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization
Navjot Singh
Deepesh Data
Jemin George
Suhas Diggavi
290
62
0
13 May 2020
Differentially Private Federated Learning with Laplacian Smoothing
Differentially Private Federated Learning with Laplacian SmoothingApplied and Computational Harmonic Analysis (ACHA), 2020
Zhicong Liang
Bao Wang
Quanquan Gu
Stanley Osher
Xingtai Lv
FedML
171
11
0
01 May 2020
Communication-Efficient Distributed Deep Learning: A Comprehensive
  Survey
Communication-Efficient Distributed Deep Learning: A Comprehensive Survey
Zhenheng Tang
Shaoshuai Shi
Wei Wang
Yue Liu
Xiaowen Chu
243
54
0
10 Mar 2020
Previous
1234
Next
Page 3 of 4