Daniel J. Lizotte

发表

Stable Dynamic Programming and Reinforcement Learning with Dual Representations

Tao Wang, Dale Schuurmans, Michael Bowling, 2007 .

Rayman Preet Singh, Daniel J. Lizotte, Peter Xiang Gao, 2012, 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm).

Bayesian sparse sampling for on-line reward optimization

Tao Wang, Dale Schuurmans, Michael H. Bowling, 2005, ICML.

Budgeted Learning of Naive-Bayes Classifiers pdf

Russell Greiner, Omid Madani, Daniel J. Lizotte, 2003, UAI.

Tracking people over time in 19th century Canada for longitudinal analysis

Maria-Luiza Antonie, Daniel J. Lizotte, Kris Inwood, 2014, Machine Learning.

Bayesian Multiple Imputation Approaches for One-Class Classification

Shehroz S. Khan, Jesse Hoey, Daniel J. Lizotte, 2012, Canadian Conference on AI.

Generative Multiple-Instance Learning Models For Quantitative Electromyography pdf

Ruth Urner, Daniel W. Stashuk, Daniel J. Lizotte, 2013, UAI.

Linear fitted-Q iteration with multiple reward functions

Susan A. Murphy, Michael H. Bowling, Daniel J. Lizotte, 2013, J. Mach. Learn. Res..

Comparisons Between Hamiltonian Monte Carlo and Maximum A Posteriori For A Bayesian Model For Apixaban Induction Dose & Dose Personalization

Daniel J. Lizotte, A. Demetri Pananos, D. Lizotte, 2020, MLHC.

Informing sequential clinical decision-making through reinforcement learning: an empirical study

Joelle Pineau, Susan A. Murphy, Daniel J. Lizotte, 2010, Machine Learning.

Archetype-Based Modeling and Search of Social Media

Kamran Sedig, Daniel J. Lizotte, Brent D. Davis, 2019, Big Data Cogn. Comput..

Visualizing Clinical Significance with Prediction and Tolerance Regions

Daniel J. Lizotte, Maria Jahja, D. Lizotte, 2017, MLHC.

Set‐valued dynamic treatment regimes for competing outcomes

Daniel J. Lizotte, Eric B. Laber, Bradley Ferguson, 2012, Biometrics.

Automatic Gait Optimization with Gaussian Process Regression

Tao Wang, Dale Schuurmans, Michael H. Bowling, 2007, IJCAI.

Improved Large Margin Dependency Parsing via Local Constraints and Laplacian Regularization

Dale Schuurmans, Qin Iris Wang, Colin Cherry, 2006, CoNLL.

Nonuniform DFT Applications in MRI: A Novel Algorithm and Parallel Implementation

Daniel J. Lizotte, Virendra C. Bhavsar, Eric Aubanel, 2003 .

The Budgeted Multi-armed Bandit Problem

Russell Greiner, Omid Madani, Daniel J. Lizotte, 2004, COLT.

Decision-Directed Data Decomposition pdf

Daniel J. Lizotte, Brent D. Davis, Ethan Jackson, 2019, ArXiv.

Active Model Selection pdf

Russell Greiner, Omid Madani, Daniel J. Lizotte, 2004, UAI.

Budgeted learning of nailve-bayes classifiers

Russell Greiner, Omid Madani, Daniel J. Lizotte, 2002, UAI 2002.

A Hybrid Design for Medical Decision Support using Data Mining to Impute Missing Data

Atif Khan, Robin Cohen, Daniel J. Lizotte, 2012 .

Integrating Machine Learning Into a Medical Decision Support System to Address the Problem of Missing Patient Data

Atif Khan, Robin Cohen, Daniel J. Lizotte, 2012, 2012 11th International Conference on Machine Learning and Applications.

Multi-Objective Markov Decision Processes for Data-Driven Decision Support

Daniel J. Lizotte, Eric B. Laber, D. Lizotte, 2016, J. Mach. Learn. Res..

Scalable approximate policies for Markov decision process models of hospital elective admissions

Jesse Hoey, Daniel J. Lizotte, George Zhu, 2014, Artif. Intell. Medicine.

Evaluating quantitative methods for intercategorical-intersectionality research: a simulation study

Daniel J. Lizotte, Mayuri Mahendran, Greta R. Bauer, 2020 .

Development and evaluation of an osteoarthritis risk model for integration into primary care health information technology

Daniel J. Lizotte, Jason E. Black, Amanda L. Terry, 2020, Int. J. Medical Informatics.

Stable Dual Dynamic Programming

Tao Wang, Dale Schuurmans, Michael H. Bowling, 2007, NIPS.

Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis

Susan A. Murphy, Michael H. Bowling, Daniel J. Lizotte, 2010, ICML.

Machine Learning for Identifying Medication-Associated Acute Kidney Injury

Sheikh S. Abdullah, Neda Rostamzadeh, Kamran Sedig, 2020, Informatics.

Reconstruction of 3-D Density Functions from Few Projections: Structural Assumptions for Graceful Degradation

Michael Cormier, Daniel J. Lizotte, Richard Mann, 2015, 2015 12th Conference on Computer and Robot Vision.

Ecological Momentary Assessment extensions 3 (EMAX3) Proposal: An app for EMA-type research

Daniel J. Lizotte, Chris Brogly, Michael A. Bauer, 2021, 2021 IEEE Symposium on Computers and Communications (ISCC).

VISEMURE: A Visual Analytics System for Making Sense of Multimorbidity Using Electronic Medical Record Data

Sheikh S. Abdullah, Kamran Sedig, Daniel J. Lizotte, 2021, Data.

Analyzing Patient Stories on Social Media Using Text Analytics

Daniel J. Lizotte, Moutasem A. Zakkar, D. Lizotte, 2021, Journal of Healthcare Informatics Research.

Rejoinder of “Dynamic treatment regimes: Technical challenges and applications”

Susan A. Murphy, Daniel J. Lizotte, Eric B. Laber, 2014, Electronic Journal of Statistics.