AAAI 2020对抗样本论文

转载知乎：https://zhuanlan.zhihu.com/p/107606590

Learning Transferable Adversarial Examples via Ghost Networks

An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation

Semantic Adversarial Diagnostic Attacks for Autonomous Applications

Joint Character Embedding and Adversarial Stability Training to Defend Adversarial Text

A New Ensemble Adversarial Attack Powered by Long-term Gradient Memories

Suspicion-Free Adversarial Attacks on Clustering Algorithms

ML-LOO: Detecting Adversarial Examples with Feature Attribution

A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks

A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models

Heuristic Black-box Adversarial Attacks on Video Recognition Models

Universal Adversarial Training

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples

CAG: A Real-time Low-cost Improved-Robustness High-transferabilitiy Content-aware Adversarial Attack Generator

Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack

Generating Adversarial Examples for Holding Robustness of Source Code Processing Models

A Robust Adversarial Training Approach to Machine Reading Comprehension

Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation

CD-UAP: Class Discriminative Universal Adversarial Perturbation

Adversary for Social Good: Protecting Familial Privacy through Joint Adversarial Attacks

Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis

Adversarial Attack on Deep Product Quantization Network for Image Retrieval

Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation

Weighted-Sampling Audio Adversarial Example Attack

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