Adversarial Learning

Hessian-based Analysis of Large Batch Training and Robustness to Adversaries NeurIPS 2018 HotFlip: White-Box Adversarial Examples for Text Classification ACL 2018 Partial Transfer Learning With Selective Adversarial Networks CVPR 2018 Provable Defenses against Adversarial Examples via the Convex Outer Adversarial Polytope ICML 2018 Robust Detection of Adversarial Attacks by Modeling the Intrinsic Properties of Deep Neural Networks NeurIPS 2018 Robustness of classifiers to uniform ℓ_p and Gaussian noise AISTATS 2018 Semantically Equivalent Adversarial Rules for Debugging NLP models ACL 2018 Spectral Signatures in Backdoor Attacks NeurIPS 2018 Towards Robust Detection of Adversarial Examples NeurIPS 2018 With Friends Like These, Who Needs Adversaries? NeurIPS 2018 Controllable Invariance through Adversarial Feature Learning NeurIPS 2017 Efficient Label Contamination Attacks Against Black-Box Learning Models IJCAI 2017 Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation NeurIPS 2017 Houdini: Fooling Deep Structured Visual and Speech Recognition Models with Adversarial Examples NeurIPS 2017 Lower bounds on the robustness to adversarial perturbations NeurIPS 2017 Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent NeurIPS 2017 Minimizing Trust Leaks for Robust Sybil Detection ICML 2017 DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks CVPR 2016 Adversarial Prediction Games for Multivariate Losses NeurIPS 2015 Feature Cross-Substitution in Adversarial Classification NeurIPS 2014 Compete to Compute NeurIPS 2013 Support Vector Machines Under Adversarial Label Noise ACML 2011 Near-Optimal Evasion of Convex-Inducing Classifiers AISTATS 2010 Nash Equilibria of Static Prediction Games NeurIPS 2009 Optimal Single-Class Classification Strategies NeurIPS 2006