Adversarial Learning

FakeTables: Using GANs to Generate Functional Dependency Preserving Tables with Bounded Real Data IJCAI 2019 Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation UAI 2019 FDA: Feature Disruptive Attack ICCV 2019 Feature Denoising for Improving Adversarial Robustness CVPR 2019 Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples CVPR 2019 Feature-Level Frankenstein: Eliminating Variations for Discriminative Recognition CVPR 2019 Feature Prioritization and Regularization Improve Standard Accuracy and Adversarial Robustness IJCAI 2019 Feature Space Perturbations Yield More Transferable Adversarial Examples CVPR 2019 Feedback Adversarial Learning: Spatial Feedback for Improving Generative Adversarial Networks CVPR 2019 FEVER Breaker’s Run of Team NbAuzDrLqg EMNLP 2019 Few-Shot Adversarial Learning of Realistic Neural Talking Head Models ICCV 2019 Finding Mixed Nash Equilibria of Generative Adversarial Networks ICML 2019 Find Me if You Can: Deep Software Clone Detection by Exploiting the Contest between the Plagiarist and the Detector AAAI 2019 First-Order Adversarial Vulnerability of Neural Networks and Input Dimension ICML 2019 Fooling Network Interpretation in Image Classification ICCV 2019 Fooling Neural Network Interpretations via Adversarial Model Manipulation NeurIPS 2019 Forward-Backward Generative Adversarial Networks for Anomaly Detection ACML 2019 Functional Adversarial Attacks NeurIPS 2019 Functional Transparency for Structured Data: a Game-Theoretic Approach ICML 2019 GAN Driven Semi-distant Supervision for Relation Extraction NAACL 2019 GCAN: Graph Convolutional Adversarial Network for Unsupervised Domain Adaptation CVPR 2019 GDPP: Learning Diverse Generations using Determinantal Point Processes ICML 2019 GEM: Generative Enhanced Model for adversarial attacks EMNLP 2019 Generalizable Adversarial Training via Spectral Normalization ICLR 2019 Generalized No Free Lunch Theorem for Adversarial Robustness ICML 2019