A parallel numerical algorithm for fredholm integro-differential two-point boundary value problems. - Ruth E. Shaw; Lawrence E. Garey; Daniel J. Lizotte (Int. J. Comput. Math., 2001)

A Parallel Numerical Algorithm for Boundary-Value FIDES on a PC Cluster. - Ruth E. Shaw; Lawrence E. Garey; Daniel J. Lizotte (IPDPS, 2002)

Budgeted Learning of Naive-Bayes Classifiers. - Daniel J. Lizotte; Omid Madani; Russell Greiner (UAI, 2003)

The Budgeted Multi-armed Bandit Problem. - Omid Madani; Daniel J. Lizotte; Russell Greiner (COLT, 2004)

Trading confidence for communications. - Daniel J. Lizotte; Hong Zhang 013 (SMC (1), 2004)

Active Model Selection. - Omid Madani; Daniel J. Lizotte; Russell Greiner (UAI, 2004)

Bayesian sparse sampling for on-line reward optimization. - Tao Wang; Daniel J. Lizotte; Michael H. Bowling; Dale Schuurmans (ICML, 2005)

Improved Large Margin Dependency Parsing via Local Constraints and Laplacian Regularization. - Qin Iris Wang; Colin Cherry; Daniel J. Lizotte; Dale Schuurmans (CoNLL, 2006)

Automatic Gait Optimization with Gaussian Process Regression. - Daniel J. Lizotte; Tao Wang; Michael H. Bowling; Dale Schuurmans (IJCAI, 2007)

Stable Dual Dynamic Programming. - Tao Wang; Daniel J. Lizotte; Michael H. Bowling; Dale Schuurmans (NIPS, 2007)

Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis. - Daniel J. Lizotte; Michael H. Bowling; Susan A. Murphy (ICML, 2010)

Convergent Fitted Value Iteration with Linear Function Approximation. - Daniel J. Lizotte (NIPS, 2011)

Informing sequential clinical decision-making through reinforcement learning: an empirical study. - Susan M. Shortreed; Eric B. Laber; Daniel J. Lizotte; T. Scott Stroup; Joelle Pineau; Susan A. Murphy (Mach. Learn., 2011)

Bayesian Multiple Imputation Approaches for One-Class Classification. - Shehroz S. Khan; Jesse Hoey; Daniel J. Lizotte (Canadian AI, 2012)

Integrating Machine Learning Into a Medical Decision Support System to Address the Problem of Missing Patient Data. - Atif Khan 001; John A. Doucette; Robin Cohen; Daniel J. Lizotte (ICMLA (1), 2012)

On hourly home peak load prediction. - Rayman Preet Singh; Peter Xiang Gao; Daniel J. Lizotte (SmartGridComm, 2012)

Set-valued dynamic treatment regimes for competing outcomes - Eric B. Laber; Daniel J. Lizotte; Bradley Ferguson (CoRR, 2012)

An experimental methodology for response surface optimization methods. - Daniel J. Lizotte; Russell Greiner; Dale Schuurmans (J. Glob. Optim., 2012)

Linear fitted-Q iteration with multiple reward functions. - Daniel J. Lizotte; Michael Bowling; Susan A. Murphy (J. Mach. Learn. Res., 2012)

Critiquing Time-of-Use pricing in Ontario. - Adedamola Adepetu; Elnaz Rezaei; Daniel J. Lizotte; Srinivasan Keshav (SmartGridComm, 2013)

Generative Multiple-Instance Learning Models For Quantitative Electromyography. - Tameem Adel; Benn Smith; Ruth Urner; Daniel W. Stashuk; Daniel J. Lizotte (UAI, 2013)

Scalable approximate policies for Markov decision process models of hospital elective admissions. - George Zhu; Daniel J. Lizotte; Jesse Hoey (Artif. Intell. Medicine, 2014)

Theory and Application of Shapelets to the Analysis of Surface Self-assembly Imaging. - Robert Suderman; Daniel J. Lizotte; Nasser Mohieddin Abukhdeir (CoRR, 2014)

Tracking people over time in 19th century Canada for longitudinal analysis. - Luiza Antonie; Kris Inwood; Daniel J. Lizotte; J. Andrew Ross (Mach. Learn., 2014)

Reconstruction of 3-D Density Functions from Few Projections: Structural Assumptions for Graceful Degradation. - Michael Cormier; Daniel J. Lizotte; Richard Mann (CRV, 2015)

gLOP: the global and Local Penalty for Capturing Predictive Heterogeneity. - Rhiannon V. Rose; Daniel J. Lizotte (MLHC, 2016)

Multi-Objective Markov Decision Processes for Data-Driven Decision Support. - Daniel J. Lizotte; Eric B. Laber (J. Mach. Learn. Res., 2016)

Visualizing Clinical Significance with Prediction and Tolerance Regions. - Maria Jahja; Daniel J. Lizotte (MLHC, 2017)

Archetype-Based Modeling and Search of Social Media. - Brent D. Davis; Kamran Sedig; Daniel J. Lizotte (Big Data Cogn. Comput., 2019)

Decision-Directed Data Decomposition. - Brent D. Davis; Ethan Jackson; Daniel J. Lizotte (CoRR, 2019)

Development of an EMG-Based Muscle Health Model for Elbow Trauma Patients. - Emma Farago; Shrikant Chinchalkar; Daniel J. Lizotte; Ana Luisa Trejos (Sensors, 2019)

Improving Access and Mental Health for Youth Through Virtual Models of Care. - Cheryl Forchuk; Sandra Fisman; Jeffrey P. Reiss; Kerry Collins; Julie Eichstedt; Abraham Rudnick; Wanrudee Isaranuwatchai; Jeffrey S. Hoch; Xianbin Wang 001; Daniel J. Lizotte; Shona Macpherson; Richard Booth 005 (ICOST, 2020)

Comparisons Between Hamiltonian Monte Carlo and Maximum A Posteriori For A Bayesian Model For Apixaban Induction Dose & Dose Personalization. - Athanasios Demetri Pananos; Daniel J. Lizotte (MLHC, 2020)

Development and evaluation of an osteoarthritis risk model for integration into primary care health information technology. - Jason E. Black; Amanda L. Terry; Daniel J. Lizotte (Int. J. Medical Informatics, 2020)

Machine Learning for Identifying Medication-Associated Acute Kidney Injury. - Sheikh S. Abdullah; Neda Rostamzadeh; Kamran Sedig; Daniel J. Lizotte; Amit X. Garg; Eric McArthur (Informatics, 2020)

A User-Centered Design of Explainable AI for Clinical Decision Support. - Mozhgan Salimiparsa; Daniel J. Lizotte; Kamran Sedig (Canadian AI, 2021)

Hierarchical Reinforcement Learning for Decision Support in Health Care. - Caroline Strickland; Daniel J. Lizotte (Canadian AI, 2021)

Ecological Momentary Assessment extensions 3 (EMAX3) Proposal: An app for EMA-type research. - Chris Brogly; Daniel J. Lizotte; Michael A. Bauer 001 (ISCC, 2021)

VISEMURE: A Visual Analytics System for Making Sense of Multimorbidity Using Electronic Medical Record Data. - Maede Nouri; Daniel J. Lizotte; Kamran Sedig; Sheikh S. Abdullah (Data, 2021)

Analyzing Patient Stories on Social Media Using Text Analytics. - Moutasem A. Zakkar; Daniel J. Lizotte (J. Heal. Informatics Res., 2021)

Smart Technology in the Home for People Living in the Community with Mental Illness and Physical Comorbidities. - Cheryl Forchuk; Abraham Rudnick; Deborah Corring; Daniel J. Lizotte; Jeffrey S. Hoch; Richard Booth 005; Barbara Frampton; Rupinder Mann; Jonathan Serrato (ICOST, 2022)

Hybrid Feature- and Similarity-Based Models for Prediction and Interpretation using Large-Scale Observational Data. - Jacqueline K. Kueper; Jennifer Rayner; Daniel J. Lizotte (CoRR, 2022)

Is primary health care ready for artificial intelligence? What do primary health care stakeholders say? - Amanda L. Terry; Jacqueline K. Kueper; Ron Beleno; Judith Belle Brown; Sonny Cejic; Janet Dang; Daniel Leger; Scott McKay; Leslie Meredith; Andrew D. Pinto; Bridget L. Ryan; Moira Stewart; et al. (BMC Medical Informatics Decis. Mak., 2022)

Reinforcement learning in large, structured action spaces: A simulation study of decision support for spinal cord injury rehabilitation. - Nathan Phelps; Stephanie Marrocco; Stephanie Cornell; Dalton L. Wolfe; Daniel J. Lizotte (CoRR, 2023)

Look-Ahead Selective Plasticity for Continual Learning of Visual Tasks. - Rouzbeh Meshkinnejad; Jie Mei; Daniel J. Lizotte; Yalda Mohsenzadeh (CoRR, 2023)

A Smart Technology Intervention in the Homes of People with Mental Illness and Physical Comorbidities. - Cheryl Forchuk; Abraham Rudnick; Deborah Corring; Daniel J. Lizotte; Jeffrey S. Hoch; Richard Booth 005; Barbara Frampton; Rupinder Mann; Jonathan Serrato (Sensors, 2023)

Challenges learning from imbalanced data using tree-based models: Prevalence estimates systematically depend on hyperparameters and can be upwardly biased. - Nathan Phelps; Daniel J. Lizotte; Douglas G. Woolford (CoRR, 2024)

DRL-GAN: A Hybrid Approach for Binary and Multiclass Network Intrusion Detection. - Caroline Strickland; Muhammad Zakar; Chandrika Saha; Sareh Nejad; Noshin Tasnim; Daniel J. Lizotte; Anwar Haque (Sensors, 2024)

Look-Ahead Selective Plasticity for Continual Learning of Visual Tasks. - Rouzbeh Meshkinnejad; Jie Mei; Zeduo Zhang; Daniel J. Lizotte; Yalda Mohsenzadeh (UniReps, 2025)

Using Platt's scaling for calibration after undersampling - limitations and how to address them. - Nathan Phelps; Daniel J. Lizotte; Douglas G. Woolford (Trans. Mach. Learn. Res., 2025)

Towards understanding the bias in decision trees. - Nathan Phelps; Daniel J. Lizotte; Douglas G. Woolford (CoRR, 2025)