Daniel Lizotte
Daniel Lizotte
Assistant Professor of Computer Science, University of Western Ontario
Verified email at uwo.ca
Cited by
Cited by
Automatic Gait Optimization with Gaussian Process Regression.
DJ Lizotte, T Wang, MH Bowling, D Schuurmans
IJCAI 7, 944-949, 2007
Practical bayesian optimization
DJ Lizotte
University of Alberta, 2008
Informing sequential clinical decision-making through reinforcement learning: an empirical study
SM Shortreed, E Laber, DJ Lizotte, TS Stroup, J Pineau, SA Murphy
Machine learning 84 (1-2), 109-136, 2011
Bayesian sparse sampling for on-line reward optimization
T Wang, D Lizotte, M Bowling, D Schuurmans
Proceedings of the 22nd international conference on Machine learning, 956-963, 2005
Dynamic treatment regimes: Technical challenges and applications
EB Laber, DJ Lizotte, M Qian, WE Pelham, SA Murphy
Electronic journal of statistics 8 (1), 1225, 2014
Budgeted learning of na´ve-Bayes classifiers
DJ Lizotte, O Madani, R Greiner
Proceedings of the Nineteenth conference on Uncertainty in Artificialá…, 2002
Efficient reinforcement learning with multiple reward functions for randomized controlled trial analysis
DJ Lizotte, MH Bowling, SA Murphy
ICML, 2010
Linear fitted-q iteration with multiple reward functions
DJ Lizotte, M Bowling, SA Murphy
The Journal of Machine Learning Research 13 (1), 3253-3295, 2012
An experimental methodology for response surface optimization methods
DJ Lizotte, R Greiner, D Schuurmans
Journal of Global Optimization 53 (4), 699-736, 2012
Set‐valued dynamic treatment regimes for competing outcomes
EB Laber, DJ Lizotte, B Ferguson
Biometrics 70 (1), 53-61, 2014
Active model selection
O Madani, DJ Lizotte, R Greiner
Proceedings of the 20th conference on Uncertainty in Artificial Intelligenceá…, 2004
Tracking people over time in 19th century Canada for longitudinal analysis
L Antonie, K Inwood, DJ Lizotte, JA Ross
Machine learning 95 (1), 129-146, 2014
The budgeted multi-armed bandit problem
O Madani, DJ Lizotte, R Greiner
International Conference on Computational Learning Theory, 643-645, 2004
On hourly home peak load prediction
RP Singh, PX Gao, DJ Lizotte
2012 IEEE Third International Conference on Smart Grid Communicationsá…, 2012
Multi-objective Markov decision processes for data-driven decision support
DJ Lizotte, EB Laber
The Journal of Machine Learning Research 17 (1), 7378-7405, 2016
Interpatient variation in rivaroxaban and apixaban plasma concentrations in routine care
M Gulilat, A Tang, SE Gryn, P Leong-Sit, AC Skanes, JE Alfonsi, ...
Canadian Journal of Cardiology 33 (8), 1036-1043, 2017
Predicting responses to platin chemotherapy agents with biochemically-inspired machine learning
EJ Mucaki, JZL Zhao, DJ Lizotte, PK Rogan
Signal transduction and targeted therapy 4 (1), 1-12, 2019
Statistical inference in dynamic treatment regimes
EB Laber, M Qian, DJ Lizotte, WE Pelham, SA Murphy
arXiv preprint arXiv:1006.5831, 2010
Stable dual dynamic programming
T Wang, M Bowling, D Schuurmans, DJ Lizotte
Advances in neural information processing systems, 1569-1576, 2008
Critiquing time-of-use pricing in Ontario
A Adepetu, E Rezaei, D Lizotte, S Keshav
2013 IEEE International Conference on Smart Grid Communicationsá…, 2013
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