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Adversarial Learning

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Papers

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data NIPS 2021
Observation-Free Attacks on Stochastic Bandits NIPS 2021
SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection NIPS 2021
Adversarially Robust Change Point Detection NIPS 2021
Probabilistic Margins for Instance Reweighting in Adversarial Training NIPS 2021
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training NIPS 2021
Not All Low-Pass Filters are Robust in Graph Convolutional Networks NIPS 2021
Adversarial Training Helps Transfer Learning via Better Representations NIPS 2021
Morié Attack (MA): A New Potential Risk of Screen Photos NIPS 2021
Robust Deep Reinforcement Learning through Adversarial Loss NIPS 2021
Gradient-Free Adversarial Training Against Image Corruption for Learning-based Steering NIPS 2021
On the Algorithmic Stability of Adversarial Training NIPS 2021
To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs NIPS 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses NIPS 2021
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks NIPS 2021
Unsupervised Speech Recognition NIPS 2021
Encoding Robustness to Image Style via Adversarial Feature Perturbations NIPS 2021
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers NIPS 2021
Adversarially robust learning for security-constrained optimal power flow NIPS 2021
Neural Architecture Dilation for Adversarial Robustness NIPS 2021
Clustering Effect of Adversarial Robust Models NIPS 2021
Data Augmentation Can Improve Robustness NIPS 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks NIPS 2021
Adversarial Examples Make Strong Poisons NIPS 2021
Adversarially Robust Imitation Learning CORL 2021