“What’s in the box?!”: Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models
Authors: Sahar Abdelnabi, Mario Fritz | Published: 2021-02-09 | Updated: 2021-03-09
モデル性能評価
$k$-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers
Authors: Djordje Slijepčević, Maximilian Henzl, Lukas Daniel Klausner, Tobias Dam, Peter Kieseberg, Matthias Zeppelzauer | Published: 2021-02-09 | Updated: 2022-06-22
Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack
Authors: Ding Sheng Ong, Chee Seng Chan, Kam Woh Ng, Lixin Fan, Qiang Yang | Published: 2021-02-08 | Updated: 2021-03-01
Optimal Transport as a Defense Against Adversarial Attacks
Authors: Quentin Bouniot, Romaric Audigier, Angélique Loesch | Published: 2021-02-05 | Updated: 2021-03-30
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
Authors: Yugeng Liu, Rui Wen, Xinlei He, Ahmed Salem, Zhikun Zhang, Michael Backes, Emiliano De Cristofaro, Mario Fritz, Yang Zhang | Published: 2021-02-04 | Updated: 2021-10-06
Adversarially Robust Learning with Unknown Perturbation Sets
Authors: Omar Montasser, Steve Hanneke, Nathan Srebro | Published: 2021-02-03
Fast Training of Provably Robust Neural Networks by SingleProp
Authors: Akhilan Boopathy, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel | Published: 2021-02-01
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning
Authors: Konstantinos P. Panousis, Sotirios Chatzis, Antonios Alexos, Sergios Theodoridis | Published: 2021-01-04 | Updated: 2021-03-29
Gradient Sparsification Can Improve Performance of Differentially-Private Convex Machine Learning
Authors: Farhad Farokhi | Published: 2020-11-30 | Updated: 2020-12-01
Voting based ensemble improves robustness of defensive models
Authors: Devvrit, Minhao Cheng, Cho-Jui Hsieh, Inderjit Dhillon | Published: 2020-11-28