Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

5 December 2017

Song Han

Papers citing "Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training"

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Title
A Survey on Federated Recommendation Systems Zehua Sun Yonghui Xu Y. Liu Weiliang He Lanju Kong Fangzhao Wu Y. Jiang Li-zhen Cui FedML 24 60 0 27 Dec 2022
Client Selection for Federated Bayesian Learning Jiarong Yang Yuan Liu Rahif Kassab FedML 33 11 0 11 Dec 2022
Vertical Federated Learning: A Structured Literature Review Afsana Khan M. T. Thij A. Wilbik FedML 50 10 0 01 Dec 2022
HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning Pengyu Qiu Xuhong Zhang S. Ji Chong Fu Xing Yang Ting Wang FedML AAML 22 12 0 01 Dec 2022
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression Xiaoyun Li Ping Li FedML 32 4 0 25 Nov 2022
Vertical Federated Learning: Concepts, Advances and Challenges Yang Liu Yan Kang Tianyuan Zou Yanhong Pu Yuanqin He Xiaozhou Ye Ye Ouyang Yaqin Zhang Qian Yang FedML 57 161 0 23 Nov 2022
Improving Federated Learning Communication Efficiency with Global Momentum Fusion for Gradient Compression Schemes Chun-Chih Kuo Ted T. Kuo Chia-Yu Lin FedML 8 1 0 17 Nov 2022
Optimal Privacy Preserving for Federated Learning in Mobile Edge Computing Hai M. Nguyen N. Chu Diep N. Nguyen D. Hoang Van-Dinh Nguyen Minh Hoàng Hà E. Dutkiewicz Marwan Krunz FedML 19 1 0 14 Nov 2022
QuantPipe: Applying Adaptive Post-Training Quantization for Distributed Transformer Pipelines in Dynamic Edge Environments Hong Wang Connor Imes Souvik Kundu P. Beerel S. Crago J. Walters MQ 13 7 0 08 Nov 2022
HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse Shenglai Zeng Zonghang Li Hongfang Yu Zhihao Zhang Long Luo Bo-wen Li Dusit Niyato 32 42 0 07 Nov 2022
Adaptive Compression for Communication-Efficient Distributed Training Maksim Makarenko Elnur Gasanov Rustem Islamov Abdurakhmon Sadiev Peter Richtárik 24 12 0 31 Oct 2022
FedGRec: Federated Graph Recommender System with Lazy Update of Latent Embeddings Junyi Li Heng-Chiao Huang FedML 24 6 0 25 Oct 2022
A simplified convergence theory for Byzantine resilient stochastic gradient descent Lindon Roberts E. Smyth 23 3 0 25 Aug 2022
Joint Privacy Enhancement and Quantization in Federated Learning Natalie Lang Elad Sofer Tomer Shaked Nir Shlezinger FedML 32 46 0 23 Aug 2022
A Fast Blockchain-based Federated Learning Framework with Compressed Communications Laizhong Cui Xiaoxin Su Yipeng Zhou FedML 14 23 0 12 Aug 2022
Towards Efficient Communications in Federated Learning: A Contemporary Survey Zihao Zhao Yuzhu Mao Yang Liu Linqi Song Ouyang Ye Xinlei Chen Wenbo Ding FedML 51 59 0 02 Aug 2022
BiFeat: Supercharge GNN Training via Graph Feature Quantization Yuxin Ma Ping Gong Jun Yi Z. Yao Cheng-rong Li Yuxiong He Feng Yan GNN 21 6 0 29 Jul 2022
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications Xingbo Fu Binchi Zhang Yushun Dong Chen Chen Jundong Li FedML OOD AI4CE 28 35 0 24 Jul 2022
Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach Naifu Zhang M. Tao Jia Wang Fan Xu 11 13 0 28 Jun 2022
Efficient Adaptive Federated Optimization of Federated Learning for IoT Zunming Chen Hongyan Cui Ensen Wu Yu Xi 27 0 0 23 Jun 2022
sqSGD: Locally Private and Communication Efficient Federated Learning Yan Feng Tao Xiong Ruofan Wu Lingjuan Lv Leilei Shi FedML 16 2 0 21 Jun 2022
Matching Pursuit Based Scheduling for Over-the-Air Federated Learning Ali Bereyhi Adela Vagollari S. Asaad R. Muller W. Gerstacker H. Vincent Poor 16 6 0 14 Jun 2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity Kiwan Maeng Haiyu Lu Luca Melis John Nguyen Michael G. Rabbat Carole-Jean Wu FedML 29 31 0 30 May 2022
Federated learning: Applications, challenges and future directions Subrato Bharati Hossain Mondal Prajoy Podder V. B. Surya Prasath FedML 39 52 0 18 May 2022
Federated Random Reshuffling with Compression and Variance Reduction Grigory Malinovsky Peter Richtárik FedML 22 10 0 08 May 2022
A review of Federated Learning in Intrusion Detection Systems for IoT Aitor Belenguer J. Navaridas J. A. Pascual 20 15 0 26 Apr 2022
FedVQCS: Federated Learning via Vector Quantized Compressed Sensing Yong-Nam Oh Yo-Seb Jeon Mingzhe Chen Walid Saad FedML 17 10 0 16 Apr 2022
Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography J. Kim Taha Toghani César A. Uribe Anastasios Kyrillidis 27 3 0 22 Mar 2022
Similarity-based Label Inference Attack against Training and Inference of Split Learning Junlin Liu Xinchen Lyu Qimei Cui Xiaofeng Tao FedML 24 26 0 10 Mar 2022
Linear Stochastic Bandits over a Bit-Constrained Channel A. Mitra Hamed Hassani George J. Pappas 34 8 0 02 Mar 2022
DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training Joya Chen Kai Xu Yuhui Wang Yifei Cheng Angela Yao 19 7 0 28 Feb 2022
BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning A. Mondal Harpreet Virk Debayan Gupta 32 15 0 06 Feb 2022
Distributed Learning With Sparsified Gradient Differences Yicheng Chen Rick S. Blum Martin Takáč Brian M. Sadler 21 15 0 05 Feb 2022
DEFER: Distributed Edge Inference for Deep Neural Networks Arjun Parthasarathy Bhaskar Krishnamachari 9 14 0 18 Jan 2022
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning Irem Ergun Hasin Us Sami Başak Güler FedML 28 25 0 23 Dec 2021
Optimal Rate Adaption in Federated Learning with Compressed Communications Laizhong Cui Xiaoxin Su Yipeng Zhou Jiangchuan Liu FedML 37 38 0 13 Dec 2021
Communication-Efficient Distributed Learning via Sparse and Adaptive Stochastic Gradient Xiaoge Deng Dongsheng Li Tao Sun Xicheng Lu FedML 18 0 0 08 Dec 2021
Communication-Efficient Federated Learning via Quantized Compressed Sensing Yong-Nam Oh Namyoon Lee Yo-Seb Jeon H. Vincent Poor FedML MQ 22 34 0 30 Nov 2021
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression Sian Jin Chengming Zhang Xintong Jiang Yunhe Feng Hui Guan Guanpeng Li S. Song Dingwen Tao 23 23 0 18 Nov 2021
Large-Scale Deep Learning Optimizations: A Comprehensive Survey Xiaoxin He Fuzhao Xue Xiaozhe Ren Yang You 24 14 0 01 Nov 2021
Federated Learning over Wireless IoT Networks with Optimized Communication and Resources Student Member Ieee Hao Chen Shaocheng Huang Deyou Zhang Ming Xiao Fellow Ieee Mikael Skoglund L. F. I. H. Vincent Poor 20 94 0 22 Oct 2021
BEV-SGD: Best Effort Voting SGD for Analog Aggregation Based Federated Learning against Byzantine Attackers Xin-Yue Fan Yue Wang Yan Huo Zhi Tian FedML 17 23 0 18 Oct 2021
Federated learning and next generation wireless communications: A survey on bidirectional relationship Debaditya Shome Omer Waqar Wali Ullah Khan 26 31 0 14 Oct 2021
ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training Hui-Po Wang Sebastian U. Stich Yang He Mario Fritz FedML AI4CE 28 46 0 11 Oct 2021
Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients Lingjiao Chen Leshang Chen Hongyi Wang S. Davidson Edgar Dobriban FedML 24 1 0 04 Oct 2021
On the Convergence of Decentralized Adaptive Gradient Methods Xiangyi Chen Belhal Karimi Weijie Zhao Ping Li 19 21 0 07 Sep 2021
FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning Zhifeng Jiang Wen Wang Yang Liu FedML 24 49 0 02 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 22 45 0 19 Aug 2021
Communication Optimization in Large Scale Federated Learning using Autoencoder Compressed Weight Updates Srikanth Chandar Pravin Chandran Raghavendra Bhat Avinash Chakravarthi AI4CE 26 3 0 12 Aug 2021
Learning a Neural Diff for Speech Models J. Macoskey Grant P. Strimel Ariya Rastrow 13 2 0 03 Aug 2021