Multi-Step Adversarial Perturbations on Recommender Systems Embeddings
Authors: Vito Walter Anelli, Alejandro Bellogín, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra | Published: 2020-10-03
敵対的摂動手法
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning
Authors: Jirong Yi, Raghu Mudumbai, Weiyu Xu | Published: 2020-07-28
Learning perturbation sets for robust machine learning
Authors: Eric Wong, J. Zico Kolter | Published: 2020-07-16 | Updated: 2020-10-08
Learning to Generate Noise for Multi-Attack Robustness
Authors: Divyam Madaan, Jinwoo Shin, Sung Ju Hwang | Published: 2020-06-22 | Updated: 2021-06-24
Headless Horseman: Adversarial Attacks on Transfer Learning Models
Authors: Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu | Published: 2020-04-20
Protecting Classifiers From Attacks. A Bayesian Approach
Authors: Victor Gallego, Roi Naveiro, Alberto Redondo, David Rios Insua, Fabrizio Ruggeri | Published: 2020-04-18
MAB-Malware: A Reinforcement Learning Framework for Attacking Static Malware Classifiers
Authors: Wei Song, Xuezixiang Li, Sadia Afroz, Deepali Garg, Dmitry Kuznetsov, Heng Yin | Published: 2020-03-06 | Updated: 2021-04-29
Confusing and Detecting ML Adversarial Attacks with Injected Attractors
Authors: Jiyi Zhang, Ee-Chien Chang, Hwee Kuan Lee | Published: 2020-03-05 | Updated: 2021-03-08
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Authors: Francesco Croce, Matthias Hein | Published: 2020-03-03 | 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