Protection Against Reconstruction and Its Applications in Private Federated Learning

3 December 2018

Papers citing "Protection Against Reconstruction and Its Applications in Private Federated Learning"

24 / 74 papers shown

Title
Design and Analysis of Uplink and Downlink Communications for Federated Learning Sihui Zheng Cong Shen Xiang Chen 39 140 0 07 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
Federated Model Distillation with Noise-Free Differential Privacy Lichao Sun Lingjuan Lyu FedML 29 106 0 11 Sep 2020
NoPeek: Information leakage reduction to share activations in distributed deep learning Praneeth Vepakomma Abhishek Singh O. Gupta Ramesh Raskar MIACV FedML 24 84 0 20 Aug 2020
Fast-Convergent Federated Learning Hung T. Nguyen Vikash Sehwag Seyyedali Hosseinalipour Christopher G. Brinton M. Chiang H. Vincent Poor FedML 28 192 0 26 Jul 2020
Breaking the Communication-Privacy-Accuracy Trilemma Wei-Ning Chen Peter Kairouz Ayfer Özgür 14 116 0 22 Jul 2020
A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective Sin Kit Lo Qinghua Lu Chen Wang Hye-Young Paik Liming Zhu FedML 48 83 0 22 Jul 2020
SPEED: Secure, PrivatE, and Efficient Deep learning Arnaud Grivet Sébert Rafael Pinot Martin Zuber Cédric Gouy-Pailler Renaud Sirdey FedML 15 20 0 16 Jun 2020
Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh Farzan Farnia Ramtin Pedarsani Ali Jadbabaie FedML OOD 32 162 0 16 Jun 2020
Topology-aware Differential Privacy for Decentralized Image Classification Shangwei Guo Tianwei Zhang Guowen Xu Hanzhou Yu Tao Xiang Yang Liu 22 18 0 14 Jun 2020
Revisiting Membership Inference Under Realistic Assumptions Bargav Jayaraman Lingxiao Wang Katherine Knipmeyer Quanquan Gu David Evans 24 147 0 21 May 2020
FedSplit: An algorithmic framework for fast federated optimization Reese Pathak Martin J. Wainwright FedML 51 182 0 11 May 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 202 436 0 04 Mar 2020
PrivacyFL: A simulator for privacy-preserving and secure federated learning Vaikkunth Mugunthan Anton Peraire-Bueno Lalana Kagal FedML 16 57 0 19 Feb 2020
Federated Extra-Trees with Privacy Preserving Yang Liu Mingxi Chen Wenxi Zhang Junbo Zhang Yu Zheng FedML 28 3 0 18 Feb 2020
A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via $f$ -Divergences S. Asoodeh Jiachun Liao Flavio du Pin Calmon O. Kosut Lalitha Sankar FedML 22 38 0 16 Jan 2020
Towards Deep Federated Defenses Against Malware in Cloud Ecosystems Josh Payne A. Kundu FedML 21 10 0 27 Dec 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 71 969 0 04 Oct 2019
Differentially Private Meta-Learning Jeffrey Li M. Khodak S. Caldas Ameet Talwalkar FedML 35 106 0 12 Sep 2019
A Federated Learning Approach for Mobile Packet Classification Evita Bakopoulou Bálint Tillman A. Markopoulou 21 30 0 30 Jul 2019
The Privacy Blanket of the Shuffle Model Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 42 236 0 07 Mar 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David Evans 15 7 0 24 Feb 2019
Lower Bounds for Locally Private Estimation via Communication Complexity John C. Duchi Ryan M. Rogers 13 93 0 01 Feb 2019
Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints Yanjun Han Ayfer Özgür Tsachy Weissman 40 90 0 23 Feb 2018