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Understanding racial bias in health using the Medical Expenditure Panel Survey data

Nov 04, 2019
Moninder Singh, Karthikeyan Natesan Ramamurthy

* 8 pages, 8 tables 

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One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

Sep 14, 2019
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang


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AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

Oct 03, 2018
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang

* 20 pages 

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Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration

Sep 21, 2018
Ritesh Noothigattu, Djallel Bouneffouf, Nicholas Mattei, Rachita Chandra, Piyush Madan, Kush Varshney, Murray Campbell, Moninder Singh, Francesca Rossi

* 8 pages, 3 figures 

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An Algorithm for the Construction of Bayesian Network Structures from Data

Mar 06, 2013
Moninder Singh, Marco Valtorta

* Appears in Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence (UAI1993) 

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