Differentially Private Federated Learning: A Client Level Perspective

20 December 2017

Papers citing "Differentially Private Federated Learning: A Client Level Perspective"

33 / 233 papers shown

Title
Private Federated Learning with Domain Adaptation Daniel W. Peterson Pallika H. Kanani Virendra J. Marathe FedML 21 81 0 13 Dec 2019
Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration Zirui Xu Zhao Yang Jinjun Xiong Xiang Chen FedML 24 58 0 03 Dec 2019
Federated Learning with Bayesian Differential Privacy Aleksei Triastcyn Boi Faltings FedML 19 174 0 22 Nov 2019
Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving Rulin Shao Hongyu Hè Hui Liu Dianbo Liu FedML OOD 25 13 0 23 Oct 2019
Abnormal Client Behavior Detection in Federated Learning Suyi Li Yong Cheng Yang Liu Wei Wang Tianjian Chen AAML 8 134 0 22 Oct 2019
Eavesdrop the Composition Proportion of Training Labels in Federated Learning Lixu Wang Shichao Xu Tianlin Li Qi Zhu FedML 22 63 0 14 Oct 2019
Differential Privacy-enabled Federated Learning for Sensitive Health Data Olivia Choudhury A. Gkoulalas-Divanis Theodoros Salonidis I. Sylla Yoonyoung Park Grace Hsu Amar K. Das FedML OOD 17 175 0 07 Oct 2019
Differentially Private Meta-Learning Jeffrey Li M. Khodak S. Caldas Ameet Talwalkar FedML 35 106 0 12 Sep 2019
Gradient Descent with Compressed Iterates Ahmed Khaled Peter Richtárik 21 22 0 10 Sep 2019
An End-to-End Encrypted Neural Network for Gradient Updates Transmission in Federated Learning Hongyu Li Tianqi Han FedML 19 32 0 22 Aug 2019
Machine Learning at the Network Edge: A Survey M. G. Sarwar Murshed Chris Murphy Daqing Hou Nazar Khan Ganesh Ananthanarayanan Faraz Hussain 38 378 0 31 Jul 2019
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges Solmaz Niknam Harpreet S. Dhillon J. H. Reed 36 599 0 30 Jul 2019
A Federated Learning Approach for Mobile Packet Classification Evita Bakopoulou Bálint Tillman A. Markopoulou 21 30 0 30 Jul 2019
YourAdvalue: Measuring Advertising Price Dynamics without Bankrupting User Privacy Michalis Pachilakis P. Papadopoulos Nikolaos Laoutaris E. Markatos N. Kourtellis 27 9 0 24 Jul 2019
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare Yiqiang Chen Jindong Wang Chaohui Yu Wen Gao Xin Qin FedML 34 704 0 22 Jul 2019
Privacy-Preserving Classification with Secret Vector Machines Valentin Hartmann Konark Modi J. M. Pujol Robert West 23 14 0 08 Jul 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 112 2,290 0 04 Jul 2019
DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM Bao Wang Quanquan Gu M. Boedihardjo Farzin Barekat Stanley J. Osher 16 25 0 28 Jun 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 6 467 0 28 May 2019
Federated Forest Yang Liu Yingting Liu Zhijie Liu Junbo Zhang Chuishi Meng Yu Zheng FedML 13 144 0 24 May 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David Evans 15 7 0 24 Feb 2019
Federated Heavy Hitters Discovery with Differential Privacy Wennan Zhu Peter Kairouz H. B. McMahan Haicheng Sun Wei Li FedML 18 106 0 22 Feb 2019
Learning Private Neural Language Modeling with Attentive Aggregation Shaoxiong Ji Shirui Pan Guodong Long Xue Li Jing Jiang Zi Huang FedML MoMe 16 136 0 17 Dec 2018
No Peek: A Survey of private distributed deep learning Praneeth Vepakomma Tristan Swedish Ramesh Raskar O. Gupta Abhimanyu Dubey SyDa FedML 30 100 0 08 Dec 2018
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 59 1,397 0 03 Dec 2018
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 63 692 0 03 Dec 2018
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning Peng Kuang Mengkai Song Zhifei Zhang Yang Song Qian Wang Hairong Qi FedML 28 776 0 03 Dec 2018
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data Eunjeong Jeong Seungeun Oh Hyesung Kim Jihong Park M. Bennis Seong-Lyun Kim FedML 28 594 0 28 Nov 2018
Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation Micah J. Sheller G. A. Reina Brandon Edwards Jason Martin Spyridon Bakas FedML 24 457 0 10 Oct 2018
Mitigating Sybils in Federated Learning Poisoning Clement Fung Chris J. M. Yoon Ivan Beschastnikh AAML 15 497 0 14 Aug 2018
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning Tribhuvanesh Orekondy Seong Joon Oh Yang Zhang Bernt Schiele Mario Fritz PICV FedML 359 37 0 15 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 87 1,455 0 10 May 2018
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge Takayuki Nishio Ryo Yonetani FedML 49 1,376 0 23 Apr 2018