Biblio

Found 16 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.
Conference Proceedings
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.
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.
Nikolaidis, S., R. Ramakrishnan, K. Gu, and J. A. Shah, "Efficient Model Learning from Joint-Action Demonstrations for Human-Robot Collaborative Tasks", ACM/IEEE International Conference on Human Robot Interaction (HRI) [Best Enabling Technology Paper], Portland, Oregon, USA, 03/2015.
Shah, J. A., J. Stedl, B. Williams, and P. Robertson, "A Fast Incremental Algorithm for Maintaining Dispatchability of Partially Controllable Plans", International Conference on Automated Planning and Scheduling (ICAPS) [32% acceptance rate], 09/2007.
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.
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.
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.
Lasota, P. A., G. F. Rossano, and J. A. Shah, "Toward Safe Close-Proximity Human-Robot Interaction with Standard Industrial Robots", IEEE International Conference on Automation Science and Engineering (CASE), 08/2014.
Journal Article
Winfield, A. F. T., S. Booth, L. A. Dennis, T. Egawa, H. Hastie, N. Jacobs, R. I. Muttram, J. I. Olszewska, F. Rajabiyazdi, A. Theodorou, et al., "IEEE P7001: a proposed standard on transparency", Frontiers in Robotics and AI, pp. 225, 2021.
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.
Thesis
Ramakrishnan, R., "Perturbation Training for Human-Robot Teams", Department of Electrical Engineering and Computer Science, vol. S.M., 2015.
Workshop Paper
Unhelkar, V. V., C. Guan, N. Roy, and J. A. Shah, "Enabling Robot Teammates to Learn Latent States of Human Collaborators", International Conference on Robotics and Automation (ICRA), Workshop on Robot Teammates Operating in Dynamic, Unstructured Environments, 05/2018.
Iqbal, T., L. D. Riek, and J. A. Shah, "Toward a Real-time Activity Segmentation Method for Human-Robot Teaming", Robotics: Science and Systems (RSS), Workshop on Towards a framework for Joint Action: What about Theory of Mind?, 06/2018.