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Sparse Random Networks for Communication-Efficient Federated Learning

30 September 2022

Deniz Gunduz

Papers citing "Sparse Random Networks for Communication-Efficient Federated Learning"

33 / 33 papers shown

Title
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models Kyeongkook Seo Dong-Jun Han Jaejun Yoo 118 1 0 11 Mar 2025
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning Nurbek Tastan Samuel Horváth Martin Takáč Karthik Nandakumar FedML 125 0 0 03 Oct 2024
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 84 49 0 19 Aug 2021
Masked Training of Neural Networks with Partial Gradients Amirkeivan Mohtashami Martin Jaggi Sebastian U. Stich 100 23 0 16 Jun 2021
Privacy Amplification Via Bernoulli Sampling Jacob Imola Kamalika Chaudhuri FedML 49 7 0 21 May 2021
An Information-Theoretic Justification for Model Pruning Berivan Isik Tsachy Weissman Albert No 127 36 0 16 Feb 2021
Time-Correlated Sparsification for Communication-Efficient Federated Learning Emre Ozfatura Kerem Ozfatura Deniz Gunduz FedML 73 49 0 21 Jan 2021
Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks Maxwell Mbabilla Aladago Lorenzo Torresani 35 10 0 16 Jan 2021
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling Vitaly Feldman Audra McMillan Kunal Talwar FedML 72 161 0 23 Dec 2020
Characterising Bias in Compressed Models Sara Hooker Nyalleng Moorosi Gregory Clark Samy Bengio Emily L. Denton 67 185 0 06 Oct 2020
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets Ang Li Jingwei Sun Binghui Wang Lin Duan Sicheng Li Yiran Chen H. Li FedML 82 127 0 07 Aug 2020
FetchSGD: Communication-Efficient Federated Learning with Sketching D. Rothchild Ashwinee Panda Enayat Ullah Nikita Ivkin Ion Stoica Vladimir Braverman Joseph E. Gonzalez Raman Arora FedML 73 367 0 15 Jul 2020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees Farzin Haddadpour Mohammad Mahdi Kamani Aryan Mokhtari M. Mahdavi FedML 79 277 0 02 Jul 2020
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient Ankit Pensia Shashank Rajput Alliot Nagle Harit Vishwakarma Dimitris Papailiopoulos 58 103 0 14 Jun 2020
rTop-k: A Statistical Estimation Approach to Distributed SGD L. P. Barnes Huseyin A. Inan Berivan Isik Ayfer Özgür 59 65 0 21 May 2020
Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning Shaoxiong Ji Wenqi Jiang A. Walid Xue Li FedML 88 66 0 21 Mar 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 259 6,261 0 10 Dec 2019
What's Hidden in a Randomly Weighted Neural Network? Vivek Ramanujan Mitchell Wortsman Aniruddha Kembhavi Ali Farhadi Mohammad Rastegari 66 357 0 29 Nov 2019
Model Pruning Enables Efficient Federated Learning on Edge Devices Yuang Jiang Shiqiang Wang Victor Valls Bongjun Ko Wei-Han Lee Kin K. Leung Leandros Tassiulas 75 462 0 26 Sep 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi 90 323 0 31 May 2019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask Hattie Zhou Janice Lan Rosanne Liu J. Yosinski UQCV 55 387 0 03 May 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 74 1,358 0 07 Mar 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 186 427 0 29 Nov 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu Wang Borja Balle S. Kasiviswanathan 85 398 0 31 Jul 2018
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences Borja Balle Gilles Barthe Marco Gaboardi 84 389 0 04 Jul 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 240 3,473 0 09 Mar 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 136 1,407 0 05 Dec 2017
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning W. Wen Cong Xu Feng Yan Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 140 989 0 22 May 2017
Sparse Communication for Distributed Gradient Descent Alham Fikri Aji Kenneth Heafield 66 741 0 17 Apr 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 306 4,646 0 18 Oct 2016
Ternary Neural Networks for Resource-Efficient AI Applications Hande Alemdar V. Leroy Adrien Prost-Boucle F. Pétrot 59 204 0 01 Sep 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,130 0 01 Jul 2016
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 326 18,625 0 06 Feb 2015