Biblio

Found 15 results
Author [ Title(Desc)] Type Year
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B
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.
C
Zhang, C., and J. A. Shah, "Co-Optimization Multi-Agent Placement with Task Assignment and Scheduling", International Joint Conferences on Artificial Intelligence (IJCAI), 07/2016.
Zhang, C., and J. A. Shah, "Co-Optimizing Task and Motion Planning", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 10/2016.
D
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.
E
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.
F
Zhang, C., and J. A. Shah, "On Fairness in Decision-Making under Uncertainty: Definitions, Computation, and Comparison", AAAI Conference on Artificial Intelligence (AAAI), 01/2015.
Zhang, C., and J. A. Shah, "Fairness in Multi-Agent Sequential Decision-Making", Neural Information Processing Systems (NIPS), 12/2014.
I
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.
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.
L
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.
P
Ramakrishnan, R., C. Zhang, and J. Shah, "Perturbation Training for Human-Robot Teams", Journal of Artificial Intelligence Research (JAIR), vol. 59, 07/2017.
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.
R
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.
S
Booth*, S., A. Shah*, Y. Zhou*, and J. Shah, "Sampling Prediction-Matching Examples in Neural Networks: A Probabilistic Programming Approach", AAAI, StarAI Workshop, 2020.
Zhou, Y., and J. Shah, "The Solvability of Interpretability Evaluation Metrics", Findings of the Association for Computational Linguistics: EACL: Association for Computational Linguistics, 05/2023.