cpSGD: Communication-efficient and differentially-private distributed SGD

27 May 2018

Sanjiv Kumar

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

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Title
SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning Design and Training Ahsan Ali Syed Zawad Paarijaat Aditya Istemi Ekin Akkus Ruichuan Chen Feng Yan 26 9 0 04 May 2022
Bridging Differential Privacy and Byzantine-Robustness via Model Aggregation Heng Zhu Qing Ling FedML 20 23 0 29 Apr 2022
Secure Distributed/Federated Learning: Prediction-Privacy Trade-Off for Multi-Agent System Mohamed Ridha Znaidi Gaurav Gupta P. Bogdan FedML 8 1 0 24 Apr 2022
How to Attain Communication-Efficient DNN Training? Convert, Compress, Correct Zhongzhu Chen Eduin E. Hernandez Yu-Chih Huang Stefano Rini MQ 24 0 0 18 Apr 2022
Differentially Private Federated Learning via Reconfigurable Intelligent Surface Yuhan Yang Yong Zhou Youlong Wu Yuanming Shi 20 25 0 31 Mar 2022
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning Wei-Ning Chen Christopher A. Choquette-Choo Peter Kairouz A. Suresh FedML 39 63 0 07 Mar 2022
Differentially Private Federated Learning with Local Regularization and Sparsification Anda Cheng Peisong Wang Xi Sheryl Zhang Jian Cheng FedML 20 70 0 07 Mar 2022
Towards Tailored Models on Private AIoT Devices: Federated Direct Neural Architecture Search Chunhui Zhang Xiaoming Yuan Qianyun Zhang Guangxu Zhu Lei Cheng Ning Zhang FedML OOD 15 15 0 23 Feb 2022
Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation Kunal Talwar FedML 33 10 0 22 Feb 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning Chuan Ma Jun Li Kang Wei Bo Liu Ming Ding Long Yuan Zhu Han H. Vincent Poor 51 42 0 18 Feb 2022
Federated Learning with Sparsified Model Perturbation: Improving Accuracy under Client-Level Differential Privacy Rui Hu Yanmin Gong Yuanxiong Guo FedML 27 62 0 15 Feb 2022
Private Read Update Write (PRUW) with Storage Constrained Databases Sajani Vithana S. Ulukus 29 13 0 07 Feb 2022
Lossy Gradient Compression: How Much Accuracy Can One Bit Buy? Sadaf Salehkalaibar Stefano Rini FedML 27 4 0 06 Feb 2022
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks Or Litany Haggai Maron David Acuna Jan Kautz Gal Chechik Sanja Fidler FedML 38 24 0 20 Jan 2022
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning Yi Zhou Parikshit Ram Theodoros Salonidis Nathalie Baracaldo Horst Samulowitz Heiko Ludwig AI4CE 37 25 0 15 Dec 2021
Personalized Federated Learning with Adaptive Batchnorm for Healthcare Wang Lu Jindong Wang Yiqiang Chen Xin Qin Renjun Xu Dimitrios Dimitriadis Tao Qin FedML OOD 24 61 0 01 Dec 2021
DP-REC: Private & Communication-Efficient Federated Learning Aleksei Triastcyn M. Reisser Christos Louizos FedML 18 16 0 09 Nov 2021
Distribution-Invariant Differential Privacy Xuan Bi Xiaotong Shen 18 13 0 08 Nov 2021
Optimal Compression of Locally Differentially Private Mechanisms Abhin Shah Wei-Ning Chen Johannes Ballé Peter Kairouz Lucas Theis 32 42 0 29 Oct 2021
Offset-Symmetric Gaussians for Differential Privacy Parastoo Sadeghi Mehdi Korki 13 8 0 13 Oct 2021
The Skellam Mechanism for Differentially Private Federated Learning Naman Agarwal Peter Kairouz Ziyu Liu FedML 16 121 0 11 Oct 2021
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 65 36 0 27 Sep 2021
Communication Efficient Generalized Tensor Factorization for Decentralized Healthcare Networks Jing Ma Qiuchen Zhang Jian Lou Li Xiong S. Bhavani Joyce C. Ho 18 0 0 03 Sep 2021
Data-Free Evaluation of User Contributions in Federated Learning Hongtao Lv Zhenzhe Zheng Tie-Mei Luo Fan Wu Shaojie Tang Lifeng Hua Rongfei Jia Chengfei Lv FedML 13 23 0 24 Aug 2021
FedJAX: Federated learning simulation with JAX Jae Hun Ro A. Suresh Ke Wu FedML 33 48 0 04 Aug 2021
Private Retrieval, Computing and Learning: Recent Progress and Future Challenges S. Ulukus Salman Avestimehr Michael C. Gastpar S. Jafar Ravi Tandon Chao Tian FedML 28 64 0 30 Jul 2021
Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning Antonious M. Girgis Deepesh Data Suhas Diggavi FedML 28 21 0 19 Jul 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
An Efficient DP-SGD Mechanism for Large Scale NLP Models Christophe Dupuy Radhika Arava Rahul Gupta Anna Rumshisky SyDa 18 35 0 14 Jul 2021
Personalized Federated Learning with Gaussian Processes Idan Achituve Aviv Shamsian Aviv Navon Gal Chechik Ethan Fetaya FedML 32 98 0 29 Jun 2021
Towards Heterogeneous Clients with Elastic Federated Learning Zichen Ma Yu Lu Zihan Lu Wenye Li Jinfeng Yi Shuguang Cui FedML 19 3 0 17 Jun 2021
Large Scale Private Learning via Low-rank Reparametrization Da Yu Huishuai Zhang Wei Chen Jian Yin Tie-Yan Liu 23 100 0 17 Jun 2021
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks Chulin Xie Minghao Chen Pin-Yu Chen Bo-wen Li FedML 33 164 0 15 Jun 2021
On the Convergence of Differentially Private Federated Learning on Non-Lipschitz Objectives, and with Normalized Client Updates Rudrajit Das Abolfazl Hashemi Sujay Sanghavi Inderjit S. Dhillon FedML 40 4 0 13 Jun 2021
Differentially Private Federated Learning via Inexact ADMM Minseok Ryu Kibaek Kim FedML 34 15 0 11 Jun 2021
Wireless Federated Learning with Limited Communication and Differential Privacy Amir Sonee Stefano Rini Yu-Chih Huang 32 10 0 01 Jun 2021
FED- $χ^2$ : Privacy Preserving Federated Correlation Test Lun Wang Qi Pang Shuai Wang D. Song FedML 25 5 0 30 May 2021
PPT: A Privacy-Preserving Global Model Training Protocol for Federated Learning in P2P Networks Qian Chen Zilong Wang Wenjing Zhang Xiaodong Lin FedML 30 16 0 30 May 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 27 630 0 20 May 2021
Personalized Semi-Supervised Federated Learning for Human Activity Recognition Riccardo Presotto Gabriele Civitarese Claudio Bettini 34 65 0 15 Apr 2021
1-bit LAMB: Communication Efficient Large-Scale Large-Batch Training with LAMB's Convergence Speed Conglong Li A. A. Awan Hanlin Tang Samyam Rajbhandari Yuxiong He 42 33 0 13 Apr 2021
Distributed Learning Systems with First-order Methods Ji Liu Ce Zhang 8 44 0 12 Apr 2021
Communication-Efficient Agnostic Federated Averaging Jae Hun Ro Mingqing Chen Rajiv Mathews M. Mohri A. Suresh FedML 17 17 0 06 Apr 2021
Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming Ziyue Huang Yuan Qiu K. Yi Graham Cormode 21 25 0 05 Apr 2021
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation Wei Ping Fan Wu Yunhui Long Luka Rimanic Ce Zhang Bo-wen Li FedML 45 63 0 20 Mar 2021
Personalized Federated Learning using Hypernetworks Aviv Shamsian Aviv Navon Ethan Fetaya Gal Chechik FedML 41 324 0 08 Mar 2021
Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation Mohamed Seif Wei-Ting Chang Ravi Tandon FedML 20 45 0 02 Mar 2021
Wide Network Learning with Differential Privacy Huanyu Zhang Ilya Mironov Meisam Hejazinia 11 26 0 01 Mar 2021
Preserved central model for faster bidirectional compression in distributed settings Constantin Philippenko Aymeric Dieuleveut 24 30 0 24 Feb 2021
Computing Differential Privacy Guarantees for Heterogeneous Compositions Using FFT A. Koskela Antti Honkela 11 20 0 24 Feb 2021