Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models
Authors: Xiao Zang, Yi Xie, Jie Chen, Bo Yuan | Published: 2020-02-12 | Updated: 2021-06-23
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
Adversarial Robustness for Code
Authors: Pavol Bielik, Martin Vechev | 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
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
Authors: Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patane, Luca Bortolussi, Guido Sanguinetti | Published: 2020-02-11 | Updated: 2020-06-24
Improving the affordability of robustness training for DNNs
Authors: Sidharth Gupta, Parijat Dube, Ashish Verma | Published: 2020-02-11 | Updated: 2020-04-30
Hardware Trust and Assurance through Reverse Engineering: A Survey and Outlook from Image Analysis and Machine Learning Perspectives
Authors: Ulbert J. Botero, Ronald Wilson, Hangwei Lu, Mir Tanjidur Rahman, Mukhil A. Mallaiyan, Fatemeh Ganji, Navid Asadizanjani, Mark M. Tehranipoor, Damon L. Woodard, Domenic Forte | Published: 2020-02-11 | Updated: 2021-04-07
Fine-grained Uncertainty Modeling in Neural Networks
Authors: Rahul Soni, Naresh Shah, Jimmy D. Moore | Published: 2020-02-11
REALM: Retrieval-Augmented Language Model Pre-Training
Authors: Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, Ming-Wei Chang | Published: 2020-02-10
SparseIDS: Learning Packet Sampling with Reinforcement Learning
Authors: Maximilian Bachl, Fares Meghdouri, Joachim Fabini, Tanja Zseby | Published: 2020-02-10 | Updated: 2020-05-04