rTop-k: A Statistical Estimation Approach to Distributed SGD

21 May 2020

Papers citing "rTop-k: A Statistical Estimation Approach to Distributed SGD"

35 / 35 papers shown

Title
Trading-off Accuracy and Communication Cost in Federated Learning Mattia Jacopo Villani Emanuele Natale Frederik Mallmann-Trenn FedML 75 0 0 18 Mar 2025
$r$ Age- $k$ : Communication-Efficient Federated Learning Using Age Factor Matin Mortaheb Priyanka Kaswan S. Ulukus FedML 18 1 0 29 Oct 2024
Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation Sajani Vithana V. Cadambe Flavio du Pin Calmon Haewon Jeong FedML 42 1 0 03 Jul 2024
Unmasking Efficiency: Learning Salient Sparse Models in Non-IID Federated Learning Riyasat Ohib Bishal Thapaliya Gintare Karolina Dziugaite Jingyu Liu Vince D. Calhoun Sergey Plis FedML 16 1 0 15 May 2024
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy Wei-Ning Chen Berivan Isik Peter Kairouz Albert No Sewoong Oh Zheng Xu 47 3 0 02 May 2024
Efficient Unbiased Sparsification Leighton Barnes Timothy Chow Emma Cohen Keith Frankston Benjamin Howard Fred Kochman Daniel Scheinerman Jeffrey VanderKam OT 24 1 0 22 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 53 10 0 29 Jan 2024
Correlation Aware Sparsified Mean Estimation Using Random Projection Shuli Jiang Pranay Sharma Gauri Joshi 19 1 0 29 Oct 2023
Adaptive Compression in Federated Learning via Side Information Berivan Isik Francesco Pase Deniz Gunduz Sanmi Koyejo Tsachy Weissman M. Zorzi FedML 26 9 0 22 Jun 2023
Timely Asynchronous Hierarchical Federated Learning: Age of Convergence Purbesh Mitra Sennur Ulukus FedML 19 0 0 21 Jun 2023
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation Berivan Isik Wei-Ning Chen Ayfer Özgür Tsachy Weissman Albert No 48 19 0 08 Jun 2023
Private Information Retrieval and Its Applications: An Introduction, Open Problems, Future Directions Sajani Vithana Zhusheng Wang S. Ulukus 25 5 0 27 Apr 2023
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation Wei-Ning Chen Danni Song Ayfer Özgür Peter Kairouz FedML 15 25 0 04 Apr 2023
Private Read-Update-Write with Controllable Information Leakage for Storage-Efficient Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 18 5 0 07 Mar 2023
Model Segmentation for Storage Efficient Private Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 21 5 0 22 Dec 2022
Rate-Privacy-Storage Tradeoff in Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 18 5 0 19 Dec 2022
ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals Rui Song Liguo Zhou Lingjuan Lyu Andreas Festag Alois C. Knoll FedML 19 5 0 11 Dec 2022
Sparse Random Networks for Communication-Efficient Federated Learning Berivan Isik Francesco Pase Deniz Gunduz Tsachy Weissman M. Zorzi FedML 70 52 0 30 Sep 2022
Private Read Update Write (PRUW) in Federated Submodel Learning (FSL): Communication Efficient Schemes With and Without Sparsification Sajani Vithana S. Ulukus FedML 13 19 0 09 Sep 2022
Private Federated Submodel Learning with Sparsification Sajani Vithana S. Ulukus FedML 22 10 0 31 May 2022
EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization Laurent Condat Kai Yi Peter Richtárik 28 20 0 09 May 2022
Improved Information Theoretic Generalization Bounds for Distributed and Federated Learning L. P. Barnes Alex Dytso H. V. Poor FedML 26 16 0 04 Feb 2022
Collaborative Learning over Wireless Networks: An Introductory Overview Emre Ozfatura Deniz Gunduz H. Vincent Poor 22 11 0 07 Dec 2021
Optimal Compression of Locally Differentially Private Mechanisms Abhin Shah Wei-Ning Chen Johannes Ballé Peter Kairouz Lucas Theis 16 42 0 29 Oct 2021
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation Divyansh Jhunjhunwala Ankur Mallick Advait Gadhikar S. Kadhe Gauri Joshi 6 10 0 14 Oct 2021
Wireless Federated Learning with Limited Communication and Differential Privacy Amir Sonee Stefano Rini Yu-Chih Huang 14 10 0 01 Jun 2021
Over-the-Air Statistical Estimation Chuan-Zheng Lee L. P. Barnes Ayfer Özgür 11 12 0 06 Mar 2021
An Information-Theoretic Justification for Model Pruning Berivan Isik Tsachy Weissman Albert No 84 35 0 16 Feb 2021
Neural Network Compression for Noisy Storage Devices Berivan Isik Kristy Choi Xin-Yang Zheng Tsachy Weissman Stefano Ermon H. P. Wong Armin Alaghi 18 13 0 15 Feb 2021
DeepReduce: A Sparse-tensor Communication Framework for Distributed Deep Learning Kelly Kostopoulou Hang Xu Aritra Dutta Xin Li A. Ntoulas Panos Kalnis 9 7 0 05 Feb 2021
Time-Correlated Sparsification for Communication-Efficient Federated Learning Emre Ozfatura Kerem Ozfatura Deniz Gunduz FedML 36 47 0 21 Jan 2021
Timely Communication in Federated Learning Baturalp Buyukates S. Ulukus FedML 32 39 0 31 Dec 2020
Distributed Sparse SGD with Majority Voting Kerem Ozfatura Emre Ozfatura Deniz Gunduz FedML 38 4 0 12 Nov 2020
Breaking the Communication-Privacy-Accuracy Trilemma Wei-Ning Chen Peter Kairouz Ayfer Özgür 6 116 0 22 Jul 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 66 6,063 0 10 Dec 2019