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07/22/2023
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
Robust reinforcement learning (RL) seeks to train policies that can perf...
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10/12/2022
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning
Recent studies reveal that a well-trained deep reinforcement learning (R...
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06/21/2022
Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems
Communication is important in many multi-agent reinforcement learning (M...
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06/09/2021
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL
Evaluating the worst-case performance of a reinforcement learning (RL) a...
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04/22/2021
InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks
The promise of Deep Neural Network (DNN) powered Internet of Thing (IoT)...
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11/06/2020
FDNAS: Improving Data Privacy and Model Diversity in AutoML
To prevent the leakage of private information while enabling automated m...
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03/29/2020
