TensorShield: Tensor-based Defense Against Adversarial Attacks on Images
Authors: Negin Entezari, Evangelos E. Papalexakis | Published: 2020-02-18
敵対的サンプル
Scalable Quantitative Verification For Deep Neural Networks
Authors: Teodora Baluta, Zheng Leong Chua, Kuldeep S. Meel, Prateek Saxena | Published: 2020-02-17 | Updated: 2021-03-23
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models
Authors: Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi | Published: 2020-02-11 | Updated: 2020-08-15
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations
Authors: Florian Tramèr, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Jörn-Henrik Jacobsen | Published: 2020-02-11 | Updated: 2020-08-04
Input Validation for Neural Networks via Runtime Local Robustness Verification
Authors: Jiangchao Liu, Liqian Chen, Antoine Mine, Ji Wang | Published: 2020-02-09 | Updated: 2024-02-13
Analysis of Random Perturbations for Robust Convolutional Neural Networks
Authors: Adam Dziedzic, Sanjay Krishnan | Published: 2020-02-08 | Updated: 2020-06-07
Renofeation: A Simple Transfer Learning Method for Improved Adversarial Robustness
Authors: Ting-Wu Chin, Cha Zhang, Diana Marculescu | Published: 2020-02-07 | Updated: 2021-04-28
Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification
Authors: Meet P. Vadera, Satya Narayan Shukla, Brian Jalaian, Benjamin M. Marlin | Published: 2020-02-07
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study
Authors: David Mickisch, Felix Assion, Florens Greßner, Wiebke Günther, Mariele Motta | Published: 2020-02-05
Defending Adversarial Attacks via Semantic Feature Manipulation
Authors: Shuo Wang, Tianle Chen, Surya Nepal, Carsten Rudolph, Marthie Grobler, Shangyu Chen | Published: 2020-02-03 | Updated: 2020-04-22