Biblio

Found 135 results
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2022
Booth, S., W. B. Knox, J. Shah, S. Niekum, P. Stone, and A. Allievi, "Extended Abstract: Graduate Student Descent Considered Harmful? A Proposal for Studying Overfitting in Reward Functions", The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, Providence, RI, 2022.
Knox, W. B., S. Hatgis-Kessell, S. Booth, S. Niekum, P. Stone, and A. Allievi, "Extended Abstract: Partial Return Poorly Explains Human Preferences", The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), Providence, RI, 2022.
Zheng, Y., S. Booth, J. Shah, and Y. Zhou, "The Irrationality of Neural Rationale Models", Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2nd Workshop on Trustworthy Natural Langauge Processing (TrustNLP), 07/2022.
Booth, S., S. Sharma, S. Chung, J. Shah, and E. L. Glassman, "Revisiting Human-Robot Teaching and Learning Through the Lens of Human Concept Learning Theory", ACM/IEEE International Conference on Human-Robot Interaction (HRI), 03/2022.
Li*, S., T. Stouraitis*, M. Gienger, S. Vijayakumar, and J. A. Shah, "Set-based State Estimation with Probabilistic Consistency Guarantee under Epistemic Uncertainty", IEEE Robotics and Automation Letters (RA-L), vol. 7, issue 3, 03/2022.
Wang, Y., N. Figueroa, S. Li, A. Shah, and J. Shah, "Temporal Logic Imitation: Learning Plan-Satisficing Motion Policies from Demonstrations", 6th Annual Conference on Robot Learning, Auckland, New Zealand, 12/2022.
Wang, Y., C-Y. Ko, and P. Agrawal, "Visual Pre-training for Navigation: What Can We Learn from Noise?", Thirty-sixth Annual Conference on Neural Information Processing Systems, New Orleans, LA, Synthetic Data for Empowering ML Research Workshop & Self-Supervised Learning Workshop, 2022.
2023
Booth, S., B. W. Knox, J. Shah, S. Niekum, P. Stone, and A. Allievi, "The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications", Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), Washington, D.C. , 02/2023.
Zhou, Y., and J. Shah, "The Solvability of Interpretability Evaluation Metrics", Findings of the Association for Computational Linguistics: EACL: Association for Computational Linguistics, 05/2023.
Horter, T., E. L. Glassman, J. Shah, and S. Booth, "Varying How We Teach: Adding Contrast Helps Humans Learn about Robot Motions", ACM/IEEE International Conference on Human-Robot Interaction (HRI), Human-Interactive Robot Learning (HIRL) , 2023.

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