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Adversarial Learning

4854 directly classified papers

Papers per year

Papers

Disentangling factors of variation in deep representation using adversarial training NIPS 2016
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning NIPS 2016
Data Poisoning Attacks on Factorization-Based Collaborative Filtering NIPS 2016
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks CVPR 2016
Evasion and Hardening of Tree Ensemble Classifiers ICML 2016
Virtual Adversarial Training Applied to Neural Higher-Order Factors for Phone Classification INTERSPEECH 2016
Adversarial Multiclass Classification: A Risk Minimization Perspective NIPS 2016
Noisy Activation Functions ICML 2016
Preserving Privacy of Continuous High-dimensional Data with Minimax Filters AISTATS 2015
Deep Neural Networks Are Easily Fooled: High Confidence Predictions for Unrecognizable Images CVPR 2015
Fighting Bandits with a New Kind of Smoothness NIPS 2015
Is Feature Selection Secure against Training Data Poisoning? ICML 2015
Response-Based Approachability with Applications to Generalized No-Regret Problems JMLR 2015
Adversarial Prediction Games for Multivariate Losses NIPS 2015
Learning and inference in the presence of corrupted inputs COLT 2015
Fictitious Self-Play in Extensive-Form Games ICML 2015
Feature Cross-Substitution in Adversarial Classification NIPS 2014
Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications ICML 2014
Online combinatorial optimization with stochastic decision sets and adversarial losses NIPS 2014
Improved Bounds for Online Learning Over the Permutahedron and Other Ranking Polytopes AISTATS 2014
Generative Adversarial Nets NIPS 2014
Reputation-based Worker Filtering in Crowdsourcing NIPS 2014
Open Problem: Adversarial Multiarmed Bandits with Limited Advice COLT 2013
Robust Sparse Regression under Adversarial Corruption ICML 2013
Direct 0-1 Loss Minimization and Margin Maximization with Boosting NIPS 2013