Biblio

Found 34 results
Author Title [ Type(Desc)] Year
Filters: Author is Julie Shah  [Clear All Filters]
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.
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.
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.
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.
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.
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.
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., C. Muise, and J. Shah, "Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively", International Joint Conference on Artificial Intelligence (IJCAI), Macau, China, 08/2019.
Pérez-D'Arpino, C., and J. Shah, "Fast Target Prediction of Human Reaching Motion for Cooperative Human-Robot Manipulation Tasks Using Time Series Classification", IEEE International Conference on Robotics and Automation (ICRA), 05/2015.
Nikolaidis, S., P. A. Lasota, Gregory Rossano, Carlos Martinez, Thomas Fuhlbrigge, and J. Shah, "Human-Robot Collaboration in Manufacturing: Quantitative Evaluation of Predictable, Convergent Joint Action", International Symposium on Robotics (ISR) [Best Paper Nomination], 10/2013.
Kotowick, K., and J. Shah, "Intelligent Sensory Modality Selection for Electronic Supportive Devices", ACM Conference on Intelligent User Interfaces (IUI), 03/2017.
Kim, B., J. Shah, and F. Doshi-Velez, "Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction", Neural Information Processing Systems (NIPS), 12/2015.
Ramakrishnan, R., E. Kamar, B. Nushi, D. Dey, J. Shah, and E. Horvitz, "Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution", Association for the Advancement of Artificial Intelligence, 01/2019.
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.
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.
Gombolay, M., X. Jessie Yang, B. Hayes, N. Seo, Z. Liu, S. Wadhwania, T. Yu, N. Shah, T. Golen, and J. Shah, "Robotic Assistance in Coordination of Patient Care", Robotics: Science and Systems (RSS), 06/2016.
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.
Kim, B., K. Patel, A. Rostamizadeh, and J. Shah, "Scalable and interpretable data representation for high-dimensional, complex data", AAAI Conference on Artificial Intelligence (AAAI), 01/2015.
Journal Article
Gombolay, M., A. Bair, C. Huang, and J. Shah, "Computational Design of Mixed-Initiative Human–Robot Teaming That Considers Human Factors: Situational Awareness, Workload, and Workflow Preferences", The International Journal of Robotics Research (IJRR), vol. 36, issue 5-7, pp. 597-617, 02/2017.
Gombolay, M., R. Jensen, J. Stigile, T. Golen, N. Shah, S-H. Son, and J. Shah, "Human-Machine Collaborative Optimization via Apprenticeship Scheduling", Journal of Artificial Intelligence Research (JAIR) (Accepted 02/2018—To Appear), 2018.
Butchibabu, A., C. Sparano-Huiban, L. Sonenberg, and J. Shah, "Implicit Coordination Strategies for Effective Team Communication", Human Factors: The Journal of the Human Factors and Ergonomics Society (HFES), vol. 58, issue 4, 06/2016.
Nikolaidis, S., P. Lasota, R. Ramakrishnan, and J. Shah, "Improved human–robot team performance through cross-training, an approach inspired by human team training practices", International Journal of Robotics Research (IJRR), vol. 34, issue 14, pp. 1711-1730, 12/2015.
Ramakrishnan, R., C. Zhang, and J. Shah, "Perturbation Training for Human-Robot Teams", Journal of Artificial Intelligence Research (JAIR), vol. 59, 07/2017.

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