Biblio

Found 34 results
Author Title Type [ Year(Desc)]
Filters: Author is Julie Shah  [Clear All Filters]
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.
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.
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.
2017
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.
Kotowick, K., and J. Shah, "Intelligent Sensory Modality Selection for Electronic Supportive Devices", ACM Conference on Intelligent User Interfaces (IUI), 03/2017.
Ramakrishnan, R., C. Zhang, and J. Shah, "Perturbation Training for Human-Robot Teams", Journal of Artificial Intelligence Research (JAIR), vol. 59, 07/2017.
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.
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.
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.
Shah, A. J., L. Blumberg, and J. Shah, "Planning for Manipulation of Interlinked Deformable Linear Objects With Applications to Aircraft Assembly", IEEE Transactions on Automation Science and Engineering (T-ASE), pp. 1-16, 03/2018.
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 the coordination of patient care", International Journal of Robotics Research (IJRR) (Accepted 02/2018—To Appear), 2018.
Shah, A., and J. Shah, "Towards Specification Learning from Demonstrations", Robotics: Science and Systems (RSS), Workshop on Learning from Demonstrations for High Level Robotics Tasks, 06/2018.
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.
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.
Zhou, Y., J. Shah, and S. Schockaert, "Learning Household Task Knowledge from WikiHow Descriptions", International Joint Conference on Artificial Intelligence (IJCAI), Workshop on Semantic Deep Learning, 08/2019.
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.
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.
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.

Pages