Proper Network Interpretability Helps Adversarial Robustness in Classification
Authors: Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel | Published: 2020-06-26 | Updated: 2020-10-21
Interpretation Method
Smoothed Geometry for Robust Attribution
Authors: Zifan Wang, Haofan Wang, Shakul Ramkumar, Matt Fredrikson, Piotr Mardziel, Anupam Datta | Published: 2020-06-11 | Updated: 2020-10-22
Evaluations and Methods for Explanation through Robustness Analysis
Authors: Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh | Published: 2020-05-31 | Updated: 2021-04-08
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Authors: Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin | Published: 2018-08-05 | Updated: 2019-02-19
CTD: Fast, Accurate, and Interpretable Method for Static and Dynamic Tensor Decompositions
Authors: Jungwoo Lee, Dongjin Choi, Lee Sael | Published: 2017-10-09