Safety

Clean-Label Backdoor Attacks on Video Recognition Models CVPR 2020 Efficient Verification of ReLU-Based Neural Networks via Dependency Analysis AAAI 2020 Learning from Interventions Using Hierarchical Policies for Safe Learning AAAI 2020 Querying to Find a Safe Policy under Uncertain Safety Constraints in Markov Decision Processes AAAI 2020 RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models EMNLP 2020 Responsive Safety in Reinforcement Learning by PID Lagrangian Methods ICML 2020 Supervised Discovery of Unknown Unknowns through Test Sample Mining (Student Abstract) AAAI 2020 TBT: Targeted Neural Network Attack With Bit Trojan CVPR 2020 Toward Operational Safety Verification of AI-Enabled CPS (Student Abstract) AAAI 2020 Certifying Geometric Robustness of Neural Networks NeurIPS 2019 Convergent Policy Optimization for Safe Reinforcement Learning NeurIPS 2019 End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks AAAI 2019 Linear Stochastic Bandits Under Safety Constraints NeurIPS 2019 Probabilistic Model Checking of Robots Deployed in Extreme Environments AAAI 2019 Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers NeurIPS 2019 Towards Reliable Learning for High Stakes Applications AAAI 2019 Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem CVPR 2019 A Lyapunov-based Approach to Safe Reinforcement Learning NeurIPS 2018 Constrained Cross-Entropy Method for Safe Reinforcement Learning NeurIPS 2018 Learning Safe Policies with Expert Guidance NeurIPS 2018 Scaling provable adversarial defenses NeurIPS 2018 Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation NeurIPS 2017 Safe Exploration in Finite Markov Decision Processes with Gaussian Processes NeurIPS 2016 Projected Natural Actor-Critic NeurIPS 2013