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Distributed Mean Estimation with Limited Communication

2 November 2016

Sanjiv Kumar

Papers citing "Distributed Mean Estimation with Limited Communication"

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Title
Unbiased Single-scale and Multi-scale Quantizers for Distributed Optimization S. Vineeth MQ 99 0 0 26 Sep 2021
Critical Learning Periods in Federated Learning Gang Yan Hao Wang Jian Li FedML 183 11 0 12 Sep 2021
Fundamental limits of over-the-air optimization: Are analog schemes optimal? Shubham K. Jha Prathamesh Mayekar Himanshu Tyagi 127 10 0 11 Sep 2021
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 220 55 0 19 Aug 2021
FedJAX: Federated learning simulation with JAX Jae Hun Ro A. Suresh Ke Wu FedML 209 54 0 04 Aug 2021
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 110 7 0 30 Jul 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 408 454 0 14 Jul 2021
A Decentralized Adaptive Momentum Method for Solving a Class of Min-Max Optimization ProblemsSignal Processing (Signal Process.), 2021 Babak Barazandeh Tianjian Huang George Michailidis 185 13 0 10 Jun 2021
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 168 55 0 08 Jun 2021
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 OOD FedML 533 58 0 18 May 2021
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 117 44 0 10 May 2021
Communication-Efficient Agnostic Federated AveragingInterspeech (Interspeech), 2021 Jae Hun Ro Mingqing Chen Rajiv Mathews M. Mohri A. Suresh FedML 232 17 0 06 Apr 2021
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 186 5 0 13 Mar 2021
Pufferfish: Communication-efficient Models At No Extra CostConference on Machine Learning and Systems (MLSys), 2021 Hongyi Wang Saurabh Agarwal Dimitris Papailiopoulos 129 67 0 05 Mar 2021
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable DevicesNeural Information Processing Systems (NeurIPS), 2021 Max Ryabinin Eduard A. Gorbunov Vsevolod Plokhotnyuk Gennady Pekhimenko 296 42 0 04 Mar 2021
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 233 51 0 28 Feb 2021
Lossless Compression of Efficient Private Local RandomizersInternational Conference on Machine Learning (ICML), 2021 Vitaly Feldman Kunal Talwar 158 42 0 24 Feb 2021
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 234 100 0 23 Feb 2021
MARINA: Faster Non-Convex Distributed Learning with CompressionInternational Conference on Machine Learning (ICML), 2021 Eduard A. Gorbunov Konstantin Burlachenko Zhize Li Peter Richtárik 242 120 0 15 Feb 2021
Distributed Online Learning for Joint Regret with Communication ConstraintsInternational Conference on Algorithmic Learning Theory (ALT), 2021 Dirk van der Hoeven Hédi Hadiji T. Erven 139 6 0 15 Feb 2021
Communication-Efficient Distributed Optimization with Quantized PreconditionersInternational Conference on Machine Learning (ICML), 2021 Foivos Alimisis Peter Davies Dan Alistarh 171 17 0 14 Feb 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure AggregationInternational Conference on Machine Learning (ICML), 2021 Peter Kairouz Ziyu Liu Thomas Steinke FedML 295 275 0 12 Feb 2021
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 FedML MQ 151 122 0 08 Feb 2021
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 164 127 0 02 Feb 2021
CosSGD: Communication-Efficient Federated Learning with a Simple Cosine-Based Quantization Yang He Hui-Po Wang M. Zenk Mario Fritz FedML MQ 193 10 0 15 Dec 2020
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 299 24 0 14 Dec 2020
Faster Non-Convex Federated Learning via Global and Local Momentum Rudrajit Das Anish Acharya Abolfazl Hashemi Sujay Sanghavi Inderjit S. Dhillon Ufuk Topcu FedML 421 91 0 07 Dec 2020
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 233 2 0 24 Nov 2020
FDNAS: Improving Data Privacy and Model Diversity in AutoML Chunhui Zhang Yongyuan Liang Xiaoming Yuan Lei Cheng FedML 74 1 0 06 Nov 2020
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! D. Kovalev Anastasia Koloskova Martin Jaggi Peter Richtárik Sebastian U. Stich 180 79 0 03 Nov 2020
Towards Tight Communication Lower Bounds for Distributed OptimisationNeural Information Processing Systems (NeurIPS), 2020 Dan Alistarh Janne H. Korhonen FedML 123 9 0 16 Oct 2020
Oort: Efficient Federated Learning via Guided Participant Selection Fan Lai Xiangfeng Zhu H. Madhyastha Mosharaf Chowdhury FedML OODD 396 312 0 12 Oct 2020
Fairness-aware Agnostic Federated LearningSDM (SDM), 2020 Wei Du Depeng Xu Xintao Wu Hanghang Tong FedML 182 147 0 10 Oct 2020
Optimal Gradient Compression for Distributed and Federated Learning Alyazeed Albasyoni M. Safaryan Laurent Condat Peter Richtárik FedML 119 69 0 07 Oct 2020
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 189 117 0 24 Sep 2020
Communication Efficient Distributed Learning with Censored, Quantized, and Generalized Group ADMM Chaouki Ben Issaid Anis Elgabli Jihong Park M. Bennis Mérouane Debbah FedML 175 13 0 14 Sep 2020
FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework Pei Fang Zhendong Cai Hui Chen Qingjiang Shi 109 6 0 05 Sep 2020
ESMFL: Efficient and Secure Models for Federated Learning Sheng Lin Chenghong Wang Hongjia Li Jieren Deng Yanzhi Wang Caiwen Ding FedML 89 6 0 03 Sep 2020
Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs Antonious M. Girgis Deepesh Data Suhas Diggavi Peter Kairouz A. Suresh FedML 167 26 0 17 Aug 2020
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 458 232 0 08 Aug 2020
Communication-Efficient Federated Learning via Optimal Client Sampling Mónica Ribero H. Vikalo FedML 155 103 0 30 Jul 2020
Breaking the Communication-Privacy-Accuracy Trilemma Wei-Ning Chen Peter Kairouz Ayfer Özgür 387 128 0 22 Jul 2020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees Farzin Haddadpour Mohammad Mahdi Kamani Aryan Mokhtari M. Mahdavi FedML 375 304 0 02 Jul 2020
D2P-Fed: Differentially Private Federated Learning With Efficient Communication Lun Wang R. Jia Dawn Song FedML 195 0 0 22 Jun 2020
Distributed Newton Can Communicate Less and Resist Byzantine Workers Avishek Ghosh R. Maity A. Mazumdar FedML 132 35 0 15 Jun 2020
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 138 24 0 12 Jun 2020
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data Deepesh Data Suhas Diggavi FedML 128 43 0 16 May 2020
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization Navjot Singh Deepesh Data Jemin George Suhas Diggavi 221 58 0 13 May 2020
Differentially Private Federated Learning with Laplacian SmoothingApplied and Computational Harmonic Analysis (ACHA), 2020 Zhicong Liang Bao Wang Quanquan Gu Stanley Osher Xingtai Lv FedML 108 11 0 01 May 2020
Communication-Efficient Distributed Deep Learning: A Comprehensive Survey Zhenheng Tang Shaoshuai Shi Wei Wang Yue Liu Xiaowen Chu 190 54 0 10 Mar 2020