Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers
Authors: Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli | Published: 2020-06-06 | Updated: 2021-12-29
学習の改善
Towards Understanding Fast Adversarial Training
Authors: Bai Li, Shiqi Wang, Suman Jana, Lawrence Carin | Published: 2020-06-04
Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization
Authors: Mayumi Ohta, Nathaniel Berger, Artem Sokolov, Stefan Riezler | Published: 2020-06-02 | Updated: 2020-06-29
Online Robustness Training for Deep Reinforcement Learning
Authors: Marc Fischer, Matthew Mirman, Steven Stalder, Martin Vechev | Published: 2019-11-03 | Updated: 2019-11-22
Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training?
Authors: Ali Shafahi, Amin Ghiasi, Furong Huang, Tom Goldstein | Published: 2019-10-25
A Note on Our Submission to Track 4 of iDASH 2019
Authors: Marcel Keller, Ke Sun | Published: 2019-10-24
Adversarial Robustness Against the Union of Multiple Perturbation Models
Authors: Pratyush Maini, Eric Wong, J. Zico Kolter | Published: 2019-09-09 | Updated: 2020-07-28
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation
Authors: Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, Pushmeet Kohli | Published: 2019-09-03 | Updated: 2019-12-20
Metric Learning for Adversarial Robustness
Authors: Chengzhi Mao, Ziyuan Zhong, Junfeng Yang, Carl Vondrick, Baishakhi Ray | Published: 2019-09-03 | Updated: 2019-10-28
Training Set Camouflage
Authors: Ayon Sen, Scott Alfeld, Xuezhou Zhang, Ara Vartanian, Yuzhe Ma, Xiaojin Zhu | Published: 2018-12-13