From Predictions to Decisions: Using Lookahead Regularization
Authors: Nir Rosenfeld, Sophie Hilgard, Sai Srivatsa Ravindranath, David C. Parkes | Published: 2020-06-20 | Updated: 2020-06-23
文献データベース
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
Authors: Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang | Published: 2020-06-20 | Updated: 2020-06-23
Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples
Authors: Josue Ortega Caro, Yilong Ju, Ryan Pyle, Sourav Dey, Wieland Brendel, Fabio Anselmi, Ankit Patel | Published: 2020-06-19 | Updated: 2023-03-08
Backdoor Attacks to Graph Neural Networks
Authors: Zaixi Zhang, Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong | Published: 2020-06-19 | Updated: 2021-12-17
Systematic Attack Surface Reduction For Deployed Sentiment Analysis Models
Authors: Josh Kalin, David Noever, Gerry Dozier | Published: 2020-06-19
A general framework for defining and optimizing robustness
Authors: Alessandro Tibo, Manfred Jaeger, Kim G. Larsen | Published: 2020-06-19 | Updated: 2021-05-29
Differentiable Language Model Adversarial Attacks on Categorical Sequence Classifiers
Authors: I. Fursov, A. Zaytsev, N. Kluchnikov, A. Kravchenko, E. Burnaev | Published: 2020-06-19
Towards an Adversarially Robust Normalization Approach
Authors: Muhammad Awais, Fahad Shamshad, Sung-Ho Bae | Published: 2020-06-19
Adversarial Attacks for Multi-view Deep Models
Authors: Xuli Sun, Shiliang Sun | Published: 2020-06-19
Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples
Authors: Kaleel Mahmood, Deniz Gurevin, Marten van Dijk, Phuong Ha Nguyen | Published: 2020-06-18 | Updated: 2021-05-20