Implicit Generative Modeling of Random Noise during Training for Adversarial Robustness
Authors: Priyadarshini Panda, Kaushik Roy | Published: 2018-07-05 | Updated: 2019-05-31
モデルの頑健性保証
Adversarial Reprogramming of Neural Networks
Authors: Gamaleldin F. Elsayed, Ian Goodfellow, Jascha Sohl-Dickstein | Published: 2018-06-28 | Updated: 2018-11-29
Adversarial Distillation of Bayesian Neural Network Posteriors
Authors: Kuan-Chieh Wang, Paul Vicol, James Lucas, Li Gu, Roger Grosse, Richard Zemel | Published: 2018-06-27
Built-in Vulnerabilities to Imperceptible Adversarial Perturbations
Authors: Thomas Tanay, Jerone T. A. Andrews, Lewis D. Griffin | Published: 2018-06-19 | Updated: 2019-05-07
Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data
Authors: Jacson Rodrigues Correia-Silva, Rodrigo F. Berriel, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos | Published: 2018-06-14
Defense Against the Dark Arts: An overview of adversarial example security research and future research directions
Authors: Ian Goodfellow | Published: 2018-06-11
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
Authors: Amartya Sanyal, Matt J. Kusner, Adrià Gascón, Varun Kanade | Published: 2018-06-09
Adversarial Attack on Graph Structured Data
Authors: Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song | Published: 2018-06-06
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Authors: Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu | Published: 2018-06-06
PAC-learning in the presence of evasion adversaries
Authors: Daniel Cullina, Arjun Nitin Bhagoji, Prateek Mittal | Published: 2018-06-05 | Updated: 2018-06-06