Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Generalized Loss-Sensitive Adversarial Learning with Manifold Margins
Adversarial Feature Learning
Improving the Robustness of Neural Networks Using K-Support Norm Based Adversarial Training
Adversarial Discriminative Domain Adaptation
Adversarial classification
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
Learning Anonymized Representations with Adversarial Neural Networks
Certified Robustness to Adversarial Examples with Differential Privacy
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary
Sitatapatra: Blocking the Transfer of Adversarial Samples
Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples
On Detecting Adversarial Perturbations
Privacy-Preserving Adversarial Networks
Design of robust classifiers for adversarial environments
Understanding Measures of Uncertainty for Adversarial Example Detection
Domain-Adversarial Neural Networks
Query Learning with Large Margin Classifiers
Adversarial Dropout for Supervised and Semi-supervised Learning
Adversarial Transfer Learning
The Limitations of Deep Learning in Adversarial Settings
Attachment style, gender, and relationship stability: A longitudinal analysis.
Association of Park Size, Distance, and Features With Physical Activity in Neighborhood Parks
Semi-supervised Learning in Gigantic Image Collections
Stimulating a blink: reduction of eye fatigue with visual stimulus
Vision-Based Offline-Online Perception Paradigm for Autonomous Driving