Biblio

Found 34 results
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Conference Proceedings
Ramakrishnan, R., E. Kamar, D. Dey, J. Shah, and E. Horvitz, "Discovering Blind Spots in Reinforcement Learning", International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 07/2018.
Booth*, S., Y. Zhou*, A. Shah, and J. Shah, "Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example", AAAI Conference on Artificial Intelligence, 2021.
Shah, A., P. Kamath, S. Li, and J. Shah, "Bayesian Inference of Temporal Task Specifications from Demonstrations", Conference on Neural Information Processing Systems, Montreal, Canada, 2018.
Kim, J., C. Muise, A. Shah, S. Agarwal, and J. Shah, "Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations", International Joint Conference on Artificial Intelligence (IJCAI), Macau, China, 08/2019.
Kim, B., C. Rudin, and J. Shah, "The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification", Neural Information Processing Systems (NIPS), 12/2014.
Gombolay, M., R. Jensen, J. Stigile, S-H. Son, and J. Shah, "Apprenticeship Scheduling: Learning to Schedule from Human Experts", International Joint Conferences on Artificial Intelligence (IJCAI), 07/2016.
Conference Paper
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.
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.
Zhou, Y., S. Booth, M. Tulio Ribeiro, and J. Shah, "Do Feature Attribution Methods Correctly Attribute Features?", Proceedings of the 36th AAAI Conference on Artificial Intelligence: AAAI, 02/2022.

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