DoCoFL: Downlink Compression for Cross-Device Federated Learning

DoCoFL: Downlink Compression for Cross-Device Federated Learning

1 February 2023

Papers citing "DoCoFL: Downlink Compression for Cross-Device Federated Learning"

18 / 18 papers shown

Title
FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching Qifan Yan Andrew Liu Shiqi He Mathias Lécuyer Ivan Beschastnikh FedML 36 0 0 21 Apr 2025
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion Zhenheng Tang Yonggang Zhang Peijie Dong Y. Cheung Amelie Chi Zhou Bo Han Xiaowen Chu FedML MoMe AI4CE 47 6 0 27 Oct 2024
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models Yao Shu Wenyang Hu S. Ng Bryan Kian Hsiang Low Fei Richard Yu FedML 35 0 0 10 Sep 2024
Mask-Encoded Sparsification: Mitigating Biased Gradients in Communication-Efficient Split Learning Wenxuan Zhou Zhihao Qu Shen-Huan Lyu Miao Cai Baoliu Ye 32 0 0 25 Aug 2024
Byzantine-resilient Federated Learning Employing Normalized Gradients on Non-IID Datasets Shiyuan Zuo Xingrun Yan Rongfei Fan Li Shen Puning Zhao Jie Xu Han Hu FedML 36 1 0 18 Aug 2024
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression Laurent Condat A. Maranjyan Peter Richtárik 39 3 0 07 Mar 2024
Blockchain-empowered Federated Learning: Benefits, Challenges, and Solutions Zeju Cai Jianguo Chen Yuting Fan Zibin Zheng Keqin Li 39 4 0 01 Mar 2024
FedImpro: Measuring and Improving Client Update in Federated Learning Zhenheng Tang Yonggang Zhang S. Shi Xinmei Tian Tongliang Liu Bo Han Xiaowen Chu FedML 13 13 0 10 Feb 2024
Optimal and Near-Optimal Adaptive Vector Quantization Ran Ben-Basat Y. Ben-Itzhak Michael Mitzenmacher S. Vargaftik MQ 16 3 0 05 Feb 2024
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes Zhen Qin Daoyuan Chen Bingchen Qian Bolin Ding Yaliang Li Shuiguang Deng FedML 32 32 0 11 Dec 2023
Momentum Provably Improves Error Feedback! Ilyas Fatkhullin A. Tyurin Peter Richtárik 26 19 0 24 May 2023
THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression Minghao Li Ran Ben-Basat S. Vargaftik Chon-In Lao Ke Xu Michael Mitzenmacher Minlan Yu Harvard University 16 15 0 16 Feb 2023
EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression Kaja Gruntkowska A. Tyurin Peter Richtárik 38 21 0 30 Sep 2022
QUIC-FL: Quick Unbiased Compression for Federated Learning Ran Ben-Basat S. Vargaftik Amit Portnoy Gil Einziger Y. Ben-Itzhak Michael Mitzenmacher FedML 64 13 0 26 May 2022
EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback Ilyas Fatkhullin Igor Sokolov Eduard A. Gorbunov Zhize Li Peter Richtárik 44 44 0 07 Oct 2021
Comfetch: Federated Learning of Large Networks on Constrained Clients via Sketching Tahseen Rabbani Brandon Yushan Feng Marco Bornstein Kyle Rui Sang Yifan Yang Arjun Rajkumar A. Varshney Furong Huang FedML 43 2 0 17 Sep 2021
DRIVE: One-bit Distributed Mean Estimation S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher OOD FedML 66 51 0 18 May 2021
NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization Ali Ramezani-Kebrya Fartash Faghri Ilya Markov V. Aksenov Dan Alistarh Daniel M. Roy MQ 57 30 0 28 Apr 2021