Biblio

Found 157 results
Author Title Type [ Year(Desc)]
Filters: First Letter Of Last Name is S  [Clear All Filters]
2019
Zhou, Y., S. Schockaert, and J. A. Shah, "Predicting ConceptNet Path Quality Using Crowdsourced Assessments of Naturalness", The Web Conference (WWW), San Francisco, CA, ACM, 05/2019.
Li, S., and J. A. Shah, "Safe and Efficient High Dimensional Motion Planning in Space-Time with Time Parameterized Prediction", International Conference on Robotics and Automation (ICRA), 05/2019.
Unhelkar*, V. V., S. Li*, and J. A. Shah, "Semi-Supervised Learning of Decision-Making Models for Human-Robot Collaboration", Conference on Robot Learning (CoRL), 10/2019.
2020
Unhelkar*, V. V., S. Li*, and J. A. Shah, "Decision-Making for Bidirectional Communication in Sequential Human-Robot Collaborative Tasks", Human-Robot Interaction (HRI), 03/2020.
Muise, C., S. Wollenstein-Betech, S. Booth, J. Shah, and Y. Khazaen, "Modeling Blackbox Agent Behaviour via Knowledge Compilation", AAAI Conference on Artificial Intelligence, Workshop on Plan, Activity, and Intent Recognition (PAIR), 2020.
Booth*, S., A. Shah*, Y. Zhou*, and J. Shah, "Sampling Prediction-Matching Examples in Neural Networks: A Probabilistic Programming Approach", AAAI, StarAI Workshop, 2020.
Booth*, S., A. Shah*, Y. Zhou*, and J. Shah, "Sampling Prediction-Matching Examples in Neural Networks: A Probabilistic Programming Approach", AAAI, StarAI Workshop, 2020.
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.
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., S. Sharma, S. Chung, J. Shah, and E. L. Glassman, "How to Understand Your Robot: A Design Space Informed by Human Concept Learning", International Conference on Robotics and Automation (ICRA), Workshop on Social Intelligence in Humans and Robots (SIHR), 05/2021.
Booth, S., S. Sharma, S. Chung, J. Shah, and E. L. Glassman, "How to Understand Your Robot: A Design Space Informed by Human Concept Learning", International Conference on Robotics and Automation (ICRA), Workshop on Social Intelligence in Humans and Robots (SIHR), 05/2021.
Li, S., N. Figueroa, A. Shah, and J. A. Shah, "Provably Safe and Efficient Motion Planning with Uncertain Human Dynamics", Robotics: Science and Systems (R:SS), 07/2021.
Li, S., N. Figueroa, A. Shah, and J. A. Shah, "Provably Safe and Efficient Motion Planning with Uncertain Human Dynamics", Robotics: Science and Systems (R:SS), 07/2021.
Li*, S., D. Park*, Y. Sung*, J. Shah, and N. Roy, "Reactive Task and Motion Planning under Temporal Logic Specifications", IEEE International Conference on Robotics and Automation (ICRA), 06/2021.
Li*, S., D. Park*, Y. Sung*, J. Shah, and N. Roy, "Reactive Task and Motion Planning under Temporal Logic Specifications", IEEE International Conference on Robotics and Automation (ICRA), 06/2021.
Zhou, Y., S. Booth, N. Figueroa, and J. Shah, "RoCUS: Robot Controller Understanding via Sampling", Conference on Robot Learning (CoRL), London, UK, Proceedings of Machine Learning Research, 11/2021.
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.
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.
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.
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.

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