Interaction is necessary for distributed learning with privacy or communication constraints

11 November 2019

Papers citing "Interaction is necessary for distributed learning with privacy or communication constraints"

6 / 6 papers shown

Title
Private Federated Statistics in an Interactive Setting Audra McMillan O. Javidbakht Kunal Talwar Elliot Briggs Mike Chatzidakis ... Paul J. Pelzl Rehan Rishi Congzheng Song Shan Wang Shundong Zhou FedML 32 6 0 18 Nov 2022
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data Jinyan Su Jinhui Xu Di Wang 21 2 0 17 Sep 2022
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
Interactive Inference under Information Constraints Jayadev Acharya C. Canonne Yuhan Liu Ziteng Sun Himanshu Tyagi 34 35 0 21 Jul 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 150 420 0 29 Nov 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 65 230 0 25 May 2018