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Adversarial Learning

4854 directly classified papers

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Papers

Image Difficulty Curriculum for Generative Adversarial Networks (CuGAN) WACV 2020
A GAN-based Tunable Image Compression System WACV 2020
Multi-Source Domain Adaptation for Visual Sentiment Classification AAAI 2020
Adversarial Blocking Bandits NIPS 2020
Towards Certificated Model Robustness Against Weight Perturbations AAAI 2020
Dynamic Network Pruning with Interpretable Layerwise Channel Selection AAAI 2020
Reinforcement Learning with Perturbed Rewards AAAI 2020
Fastened CROWN: Tightened Neural Network Robustness Certificates AAAI 2020
ActiveThief: Model Extraction Using Active Learning and Unannotated Public Data AAAI 2020
Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits NIPS 2020
Parameterised Resource-Bounded ATL AAAI 2020
CatGAN: Category-Aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation AAAI 2020
A Robust Adversarial Training Approach to Machine Reading Comprehension AAAI 2020
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment AAAI 2020
Dual Adversarial Co-Learning for Multi-Domain Text Classification AAAI 2020
Adversarial Sparse Transformer for Time Series Forecasting NIPS 2020
Attentive User-Engaged Adversarial Neural Network for Community Question Answering AAAI 2020
Posterior-GAN: Towards Informative and Coherent Response Generation with Posterior Generative Adversarial Network AAAI 2020
Privacy Enhanced Multimodal Neural Representations for Emotion Recognition AAAI 2020
Large-Scale Adversarial Training for Vision-and-Language Representation Learning NIPS 2020
Fighting Copycat Agents in Behavioral Cloning from Observation Histories NIPS 2020
Do Adversarially Robust ImageNet Models Transfer Better? NIPS 2020
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework NIPS 2020
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles NIPS 2020
Adversarial Robustness of Supervised Sparse Coding NIPS 2020