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Published in ITSC, 2022
This paper is about perfomring anomally detection using LP Inverse Reinforcement Learning.
Recommended citation: Li, D., Shehab, M. L., Liu, Z., Aréchiga, N., DeCastro, J., & Ozay, N. (2022, October). Outlier-robust inverse reinforcement learning and reward-based detection of anomalous driving behaviors. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) (pp. 4175-4182). IEEE.
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Published in L4DC, 2024
This paper is about the Identifiability of Max Entropy Inverse Reinforcement Learning.
Recommended citation: Shehab, M. L., Aspeel, A., Aréchiga, N., Best, A., & Ozay, N. (2024, June). Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning. In 6th Annual Learning for Dynamics & Control Conference (pp. 1266-1277). PMLR.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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