An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning
Authors: Xue Yang, Yan Feng, Weijun Fang, Jun Shao, Xiaohu Tang, Shu-Tao Xia, Rongxing Lu | Published: 2020-02-23 | Updated: 2021-08-15
Federated Learning
Federated Learning with Matched Averaging
Authors: Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris Papailiopoulos, Yasaman Khazaeni | Published: 2020-02-15
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
Authors: Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh | Published: 2019-10-14 | Updated: 2021-04-09
Privacy-Preserving Classification with Secret Vector Machines
Authors: Valentin Hartmann, Konark Modi, Josep M. Pujol, Robert West | Published: 2019-07-08 | Updated: 2020-08-19
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model
Authors: Badih Ghazi, Rasmus Pagh, Ameya Velingker | Published: 2019-06-19 | Updated: 2019-12-02
SLSGD: Secure and Efficient Distributed On-device Machine Learning
Authors: Cong Xie, Sanmi Koyejo, Indranil Gupta | Published: 2019-03-16 | Updated: 2019-10-01
Federated Optimization in Heterogeneous Networks
Authors: Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith | Published: 2018-12-14 | Updated: 2020-04-21
Reaching Data Confidentiality and Model Accountability on the CalTrain
Authors: Zhongshu Gu, Hani Jamjoom, Dong Su, Heqing Huang, Jialong Zhang, Tengfei Ma, Dimitrios Pendarakis, Ian Molloy | Published: 2018-12-07
A Hybrid Approach to Privacy-Preserving Federated Learning
Authors: Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, Yi Zhou | Published: 2018-12-07 | Updated: 2019-08-14
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
Authors: Milad Nasr, Reza Shokri, Amir Houmansadr | Published: 2018-12-03 | Updated: 2020-06-06