Adversarial Attacks on Machine Learning Systems for High-Frequency Trading
Authors: Micah Goldblum, Avi Schwarzschild, Ankit B. Patel, Tom Goldstein | Published: 2020-02-21 | Updated: 2021-10-29
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Robustness from Simple Classifiers
Authors: Sharon Qian, Dimitris Kalimeris, Gal Kaplun, Yaron Singer | Published: 2020-02-21
Adversarial Detection and Correction by Matching Prediction Distributions
Authors: Giovanni Vacanti, Arnaud Van Looveren | Published: 2020-02-21
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
Authors: Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu | Published: 2020-02-21 | Updated: 2020-10-20
Enhanced Adversarial Strategically-Timed Attacks against Deep Reinforcement Learning
Authors: Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Yi Ouyang, I-Te Danny Hung, Chin-Hui Lee, Xiaoli Ma | Published: 2020-02-20
A Bayes-Optimal View on Adversarial Examples
Authors: Eitan Richardson, Yair Weiss | Published: 2020-02-20 | Updated: 2021-03-17
On the Decision Boundaries of Neural Networks: A Tropical Geometry Perspective
Authors: Motasem Alfarra, Adel Bibi, Hasan Hammoud, Mohamed Gaafar, Bernard Ghanem | Published: 2020-02-20 | Updated: 2022-08-22
Towards Certifiable Adversarial Sample Detection
Authors: Ilia Shumailov, Yiren Zhao, Robert Mullins, Ross Anderson | Published: 2020-02-20
Boosting Adversarial Training with Hypersphere Embedding
Authors: Tianyu Pang, Xiao Yang, Yinpeng Dong, Kun Xu, Jun Zhu, Hang Su | Published: 2020-02-20 | Updated: 2020-11-25
Data Heterogeneity Differential Privacy: From Theory to Algorithm
Authors: Yilin Kang, Jian Li, Yong Liu, Weiping Wang | Published: 2020-02-20 | Updated: 2023-01-28