Stealing Black-Box Functionality Using The Deep Neural Tree Architecture
Authors: Daniel Teitelman, Itay Naeh, Shie Mannor | Published: 2020-02-23
Literature Database
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning
Authors: Xue Yang, Yan Feng, Weijun Fang, Jun Shao, Xiaohu Tang, Shu-Tao Xia, Rongxing Lu | Published: 2020-02-23 | Updated: 2021-08-15
Neuron Shapley: Discovering the Responsible Neurons
Authors: Amirata Ghorbani, James Zou | Published: 2020-02-23 | Updated: 2020-11-13
Non-Intrusive Detection of Adversarial Deep Learning Attacks via Observer Networks
Authors: Kirthi Shankar Sivamani, Rajeev Sahay, Aly El Gamal | Published: 2020-02-22
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers
Authors: Chen Zhu, Renkun Ni, Ping-yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein | Published: 2020-02-22
Using Single-Step Adversarial Training to Defend Iterative Adversarial Examples
Authors: Guanxiong Liu, Issa Khalil, Abdallah Khreishah | Published: 2020-02-22 | Updated: 2020-02-27
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
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