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Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible


Jan 13, 2021
Melanie F. Pradier, Javier Zazo, Sonali Parbhoo, Roy H. Perlis, Maurizio Zazzi, Finale Doshi-Velez

* 10 pages, 5 figures, 4 tables, AMIA 2021 Virtual Informatics Summit 

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Prediction-Constrained Topic Models for Antidepressant Recommendation


Dec 01, 2017
Michael C. Hughes, Gabriel Hope, Leah Weiner, Thomas H. McCoy, Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez

* Accepted poster at NIPS 2017 Workshop on Machine Learning for Health (https://ml4health.github.io/2017/

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Prediction-Constrained Training for Semi-Supervised Mixture and Topic Models


Jul 23, 2017
Michael C. Hughes, Leah Weiner, Gabriel Hope, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez


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