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Adversarial Learning

4,859 papers

Papers per year

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588
561
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Papers

Measuring Neural Net Robustness with Constraints NIPS 2016
Blind Attacks on Machine Learners NIPS 2016
Adversarial Multiclass Classification: A Risk Minimization Perspective NIPS 2016
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning NIPS 2016
Disentangling factors of variation in deep representation using adversarial training NIPS 2016
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks CVPR 2016
Minimizing the Maximal Loss: How and Why ICML 2016
Efficient Algorithms for Adversarial Contextual Learning ICML 2016
Evasion and Hardening of Tree Ensemble Classifiers ICML 2016
Noisy Activation Functions ICML 2016
Adversarial Multi-Task Learning of Deep Neural Networks for Robust Speech Recognition INTERSPEECH 2016
Virtual Adversarial Training Applied to Neural Higher-Order Factors for Phone Classification INTERSPEECH 2016
Domain-Adversarial Training of Neural Networks JMLR 2016
Fighting Bandits with a New Kind of Smoothness NIPS 2015
Adversarial Prediction Games for Multivariate Losses NIPS 2015
Preserving Privacy of Continuous High-dimensional Data with Minimax Filters AISTATS 2015
Learning and inference in the presence of corrupted inputs COLT 2015
Deep Neural Networks Are Easily Fooled: High Confidence Predictions for Unrecognizable Images CVPR 2015
Fictitious Self-Play in Extensive-Form Games ICML 2015
Is Feature Selection Secure against Training Data Poisoning? ICML 2015
Response-Based Approachability with Applications to Generalized No-Regret Problems JMLR 2015
Online combinatorial optimization with stochastic decision sets and adversarial losses NIPS 2014
Feature Cross-Substitution in Adversarial Classification NIPS 2014
Reputation-based Worker Filtering in Crowdsourcing NIPS 2014
Generative Adversarial Nets NIPS 2014