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Hybrid Feature- and Similarity-Based Models for Prediction and Interpretation using Large-Scale Observational Data


Apr 12, 2022
Jacqueline K. Kueper, Jennifer Rayner, Daniel J. Lizotte

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Decision-Directed Data Decomposition


Sep 18, 2019
Brent D. Davis, Ethan Jackson, Daniel J. Lizotte

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On Prediction and Tolerance Intervals for Dynamic Treatment Regimes


Apr 24, 2017
Daniel J. Lizotte, Arezoo Tahmasebi

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gLOP: the global and Local Penalty for Capturing Predictive Heterogeneity


Jul 29, 2016
Rhiannon V. Rose, Daniel J. Lizotte

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* Presented at 2016 Machine Learning and Healthcare Conference (MLHC 2016), Los Angeles, CA 

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Generative Multiple-Instance Learning Models For Quantitative Electromyography


Sep 26, 2013
Tameem Adel, Benn Smith, Ruth Urner, Daniel Stashuk, Daniel J. Lizotte

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* Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013) 

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Budgeted Learning of Naive-Bayes Classifiers


Oct 19, 2012
Daniel J. Lizotte, Omid Madani, Russell Greiner

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* Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003) 

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Set-valued dynamic treatment regimes for competing outcomes


Aug 07, 2012
Eric B. Laber, Daniel J. Lizotte, Bradley Ferguson

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Active Model Selection


Jul 11, 2012
Omid Madani, Daniel J. Lizotte, Russell Greiner

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* Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004) 

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