A Fully Private Pipeline for Deep Learning on Electronic Health Records
Authors: Edward Chou, Thao Nguyen, Josh Beal, Albert Haque, Li Fei-Fei | Published: 2018-11-25
Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning
Authors: Muhammad Shayan, Clement Fung, Chris J. M. Yoon, Ivan Beschastnikh | Published: 2018-11-24 | Updated: 2019-12-12
Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting
Authors: Clement Fung, Jamie Koerner, Stewart Grant, Ivan Beschastnikh | Published: 2018-11-23 | Updated: 2019-02-24
FALCON: A Fourier Transform Based Approach for Fast and Secure Convolutional Neural Network Predictions
Authors: Shaohua Li, Kaiping Xue, Chenkai Ding, Xindi Gao, David S L Wei, Tao Wan, Feng Wu | Published: 2018-11-20
Convolutional Neural Networks with Transformed Input based on Robust Tensor Network Decomposition
Authors: Jenn-Bing Ong, Wee-Keong Ng, C. -C. Jay Kuo | Published: 2018-11-20 | Updated: 2018-12-11
Lightweight Lipschitz Margin Training for Certified Defense against Adversarial Examples
Authors: Hajime Ono, Tsubasa Takahashi, Kazuya Kakizaki | Published: 2018-11-20
Private Selection from Private Candidates
Authors: Jingcheng Liu, Kunal Talwar | Published: 2018-11-19
How to Use Heuristics for Differential Privacy
Authors: Seth Neel, Aaron Roth, Zhiwei Steven Wu | Published: 2018-11-19
The Taboo Trap: Behavioural Detection of Adversarial Samples
Authors: Ilia Shumailov, Yiren Zhao, Robert Mullins, Ross Anderson | Published: 2018-11-18 | Updated: 2019-11-21
Regularized adversarial examples for model interpretability
Authors: Yoel Shoshan, Vadim Ratner | Published: 2018-11-18 | Updated: 2018-11-21