Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
Authors: Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang | Published: 2020-06-20 | Updated: 2020-06-23
機械学習のプライバシー保護
CryptoNAS: Private Inference on a ReLU Budget
Authors: Zahra Ghodsi, Akshaj Veldanda, Brandon Reagen, Siddharth Garg | Published: 2020-06-15 | Updated: 2021-05-13
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators
Authors: Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz | Published: 2020-06-15 | Updated: 2021-03-15
Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention
Authors: Ce Ju, Ruihui Zhao, Jichao Sun, Xiguang Wei, Bo Zhao, Yang Liu, Hongshan Li, Tianjian Chen, Xinwei Zhang, Dashan Gao, Ben Tan, Han Yu, Chuning He, Yuan Jin | Published: 2020-06-15 | Updated: 2020-12-15
QEBA: Query-Efficient Boundary-Based Blackbox Attack
Authors: Huichen Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, Bo Li | Published: 2020-05-28
Information-Theoretic Bounds on the Generalization Error and Privacy Leakage in Federated Learning
Authors: Semih Yagli, Alex Dytso, H. Vincent Poor | Published: 2020-05-05
When Machine Unlearning Jeopardizes Privacy
Authors: Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang | Published: 2020-05-05 | Updated: 2021-09-14
Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging
Authors: Luis Muñoz-González, Kenneth T. Co, Emil C. Lupu | Published: 2019-09-11
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
Authors: Bingzhe Wu, Shiwan Zhao, ChaoChao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou | Published: 2019-08-21 | Updated: 2019-09-25
AdaCliP: Adaptive Clipping for Private SGD
Authors: Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar | Published: 2019-08-20 | Updated: 2019-10-23