Biblio

Found 157 results
Author Title [ Type(Desc)] Year
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Conference Paper
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.
Zhou, Y., M. Tulio Ribeiro, and J. Shah, "ExSum: From Local Explanations to Model Understanding", Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL): Association for Computational Linguistics, 07/2022.
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.
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.
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.
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.
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., 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.
Conference Proceedings
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.
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.
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.
Kim, J., and J. A. Shah, "Automatic Prediction of Consistency among Team Members' Understanding of Group Decisions in Meetings", IEEE International Conference on Systems, Man, and Cybernetics (SMC), 10/2014.
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.
Lasota, P. A., and J. A. Shah, "Bayesian Estimator for Partial Trajectory Alignment", Robotics: Science and Systems [31% Acceptance Rate], 06/2019.
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, 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.
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.
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.
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.
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.
Pérez-D'Arpino, C., and J. A. Shah, "C-LEARN: Learning Geometric Constraints from Demonstrations for Multi-Step Manipulation in Shared Autonomy", IEEE International Conference on Robotics and Automation (ICRA), 05/2017.
Kim, J., C. J. Banks, and J. A. Shah, "Collaborative Planning with Encoding of Users’ High-level Strategies", AAAI Conference on Artificial Intelligence (AAAI), 02/2017.
Unhelkar, V. V., H. Chit Siu, and J. A. Shah, "Comparative Performance of Human and Mobile Robotic Assistants in Collaborative Fetch-and-Deliver Tasks", ACM/IEEE International Conference on Human Robot Interaction (HRI), 03/2014.
Unhelkar, V. V., H. Chit Siu, and J. A. Shah, "Comparative Performance of Human and Mobile Robotic Assistants in Collaborative Fetch-and-Deliver Tasks", ACM/IEEE International Conference on Human Robot Interaction (HRI), 03/2014.

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