cpSGD: Communication-efficient and differentially-private distributed SGD

27 May 2018

Sanjiv Kumar

Papers citing "cpSGD: Communication-efficient and differentially-private distributed SGD"

50 / 238 papers shown

Title
Lossless Compression of Efficient Private Local Randomizers Vitaly Feldman Kunal Talwar 16 40 0 24 Feb 2021
Learner-Private Convex Optimization Jiaming Xu Kuang Xu Dana Yang FedML 19 2 0 23 Feb 2021
Sustainable Federated Learning Başak Güler Aylin Yener 16 13 0 22 Feb 2021
Peering Beyond the Gradient Veil with Distributed Auto Differentiation Bradley T. Baker Aashis Khanal Vince D. Calhoun Barak A. Pearlmutter Sergey Plis 23 1 0 18 Feb 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation Peter Kairouz Ziyu Liu Thomas Steinke FedML 44 232 0 12 Feb 2021
Energy-Harvesting Distributed Machine Learning Başak Güler Aylin Yener FedML 23 15 0 10 Feb 2021
Enabling Binary Neural Network Training on the Edge Erwei Wang James J. Davis Daniele Moro Piotr Zielinski Jia Jie Lim C. Coelho S. Chatterjee P. Cheung George A. Constantinides MQ 20 24 0 08 Feb 2021
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed Hanlin Tang Shaoduo Gan A. A. Awan Samyam Rajbhandari Conglong Li Xiangru Lian Ji Liu Ce Zhang Yuxiong He AI4CE 45 84 0 04 Feb 2021
Differential Privacy Meets Federated Learning under Communication Constraints Nima Mohammadi Jianan Bai Q. Fan Yifei Song Yuhao Yi Lingjia Liu FedML 12 28 0 28 Jan 2021
Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information Qi Chang Zhennan Yan L. Baskaran Hui Qu Yikai Zhang Tong Zhang Shaoting Zhang Dimitris N. Metaxas MedIm 21 12 0 15 Dec 2020
Quantizing data for distributed learning Osama A. Hanna Yahya H. Ezzeldin Christina Fragouli Suhas Diggavi FedML 39 20 0 14 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
MYSTIKO : : Cloud-Mediated, Private, Federated Gradient Descent K.R. Jayaram Archit Verma A. Verma Gegi Thomas Colin Sutcher-Shepard FedML 11 11 0 01 Dec 2020
Adaptive Federated Dropout: Improving Communication Efficiency and Generalization for Federated Learning Nader Bouacida Jiahui Hou H. Zang Xin Liu FedML 25 75 0 08 Nov 2020
FDNAS: Improving Data Privacy and Model Diversity in AutoML Chunhui Zhang Yongyuan Liang Xiaoming Yuan Lei Cheng FedML 14 1 0 06 Nov 2020
Federated Learning From Big Data Over Networks Y. Sarcheshmehpour M. Leinonen A. Jung FedML 6 17 0 27 Oct 2020
Fairness-aware Agnostic Federated Learning Wei Du Depeng Xu Xintao Wu Hanghang Tong FedML 10 128 0 10 Oct 2020
Voting-based Approaches For Differentially Private Federated Learning Yuqing Zhu Xiang Yu Yi-Hsuan Tsai Francesco Pittaluga M. Faraki Manmohan Chandraker Yu-Xiang Wang FedML 21 21 0 09 Oct 2020
Strengthening Order Preserving Encryption with Differential Privacy Amrita Roy Chowdhury Bolin Ding S. Jha Weiran Liu Jingren Zhou 20 8 0 11 Sep 2020
Hybrid Differentially Private Federated Learning on Vertically Partitioned Data Chang Wang Jian Liang Mingkai Huang Bing Bai Kun Bai Hao Li FedML 23 44 0 06 Sep 2020
ESMFL: Efficient and Secure Models for Federated Learning Sheng Lin Chenghong Wang Hongjia Li Jieren Deng Yanzhi Wang Caiwen Ding FedML 13 5 0 03 Sep 2020
APMSqueeze: A Communication Efficient Adam-Preconditioned Momentum SGD Algorithm Hanlin Tang Shaoduo Gan Samyam Rajbhandari Xiangru Lian Ji Liu Yuxiong He Ce Zhang 25 8 0 26 Aug 2020
Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs Antonious M. Girgis Deepesh Data Suhas Diggavi Peter Kairouz A. Suresh FedML 26 25 0 17 Aug 2020
A Survey on Large-scale Machine Learning Meng Wang Weijie Fu Xiangnan He Shijie Hao Xindong Wu 19 109 0 10 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 34 215 0 08 Aug 2020
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence Tianqing Zhu Dayong Ye Wei Wang Wanlei Zhou Philip S. Yu SyDa 34 125 0 05 Aug 2020
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization Rui Hu Yanmin Gong Yuanxiong Guo FedML 18 54 0 01 Aug 2020
Fast-Convergent Federated Learning Hung T. Nguyen Vikash Sehwag Seyyedali Hosseinalipour Christopher G. Brinton M. Chiang H. Vincent Poor FedML 26 192 0 26 Jul 2020
Breaking the Communication-Privacy-Accuracy Trilemma Wei-Ning Chen Peter Kairouz Ayfer Özgür 14 116 0 22 Jul 2020
Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach Yi Liu S. Garg Jiangtian Nie Yan Zhang Zehui Xiong Jiawen Kang M. S. Hossain FedML 31 378 0 19 Jul 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 28 361 0 15 Jul 2020
Differentially private cross-silo federated learning Mikko A. Heikkilä A. Koskela Kana Shimizu Samuel Kaski Antti Honkela FedML 23 24 0 10 Jul 2020
D2P-Fed: Differentially Private Federated Learning With Efficient Communication Lun Wang R. Jia Dawn Song FedML 11 0 0 22 Jun 2020
Differentially-private Federated Neural Architecture Search Ishika Singh Haoyi Zhou Kunlin Yang Mengxiao Ding Bill Lin P. Xie FedML 10 22 0 16 Jun 2020
Personalized Federated Learning with Moreau Envelopes Canh T. Dinh N. H. Tran Tuan Dung Nguyen FedML 39 967 0 16 Jun 2020
An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private Averaging C. Sabater A. Bellet J. Ramon FedML 21 18 0 12 Jun 2020
Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT A. Koskela Joonas Jälkö Lukas Prediger Antti Honkela 10 57 0 12 Jun 2020
Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data Qi Chang Hui Qu Yikai Zhang M. Sabuncu Chao Chen Tong Zhang Dimitris N. Metaxas MedIm 34 78 0 29 May 2020
Continual Local Training for Better Initialization of Federated Models Xin Yao Lifeng Sun FedML 14 71 0 26 May 2020
Efficient Federated Learning over Multiple Access Channel with Differential Privacy Constraints Amir Sonee Stefano Rini 11 16 0 15 May 2020
Differentially Private Federated Learning with Laplacian Smoothing Zhicong Liang Bao Wang Quanquan Gu Stanley Osher Yuan Yao FedML 12 7 0 01 May 2020
Hierarchically Fair Federated Learning Jingfeng Zhang Cheng Li A. Robles-Kelly Mohan Kankanhalli FedML 12 56 0 22 Apr 2020
Federated Learning with Only Positive Labels Felix X. Yu A. S. Rawat A. Menon Sanjiv Kumar FedML 11 109 0 21 Apr 2020
Communication Efficient Federated Learning with Energy Awareness over Wireless Networks Richeng Jin Xiaofan He H. Dai 36 25 0 15 Apr 2020
Concentrated Differentially Private and Utility Preserving Federated Learning Rui Hu Yuanxiong Guo Yanmin Gong FedML 38 12 0 30 Mar 2020
Differentially Private Federated Learning for Resource-Constrained Internet of Things Rui Hu Yuanxiong Guo E. Ratazzi Yanmin Gong FedML 33 17 0 28 Mar 2020
FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection Ruixuan Liu Yang Cao Masatoshi Yoshikawa Hong Chen FedML 6 106 0 24 Mar 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 202 434 0 04 Mar 2020
Differentially Private Deep Learning with Smooth Sensitivity Lichao Sun Yingbo Zhou Philip S. Yu Caiming Xiong FedML 21 9 0 01 Mar 2020
Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees Richeng Jin Yufan Huang Xiaofan He H. Dai Tianfu Wu FedML 22 63 0 25 Feb 2020