Publications

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Author Keyword Title Type [ Year(Asc)]
2017
Subramanian, S.Ganapathi & Crowley, M., 2017. Learning Forest Wildfire Dynamics from Satellite Images Using Reinforcement Learning. In Conference on Reinforcement Learning and Decision Making. Ann Arbor, MI, USA.
Maryam, S. et al., 2017. Application of Probabilistically-Weighted Graphs to Image-Based Diagnosis of Alzheimer’s Disease using Diffusion MRI. In SPIE Medical Imaging Conference on Computer-Aided Diagnosis. March 3. Orlando, FL, United States: International Society for Optics and Photonics. Available at: http://dx.doi.org/10.1117/12.2254164.
2016
Salem, M., Crowley, M. & Fischmeister, S., 2016. Anomaly Detection Using Inter-Arrival Curves for Real-time Systems. In 2016 28th Euromicro Conference on Real-Time Systems. jul. Toulouse, France, pp. 97–106.
Salem, M., Crowley, M. & Fischmeister, S., 2016. Inter-Arrival Curves for Multi-Mode and Online Anomaly Detection. In Euromicro Conference on Real-Time Systems 2016 - Work-in-Progress Proceedings. Toulouse, France.
2015
Crowley, M., 2015. Answering Simple Questions About Spatially Spreading Systems. In 2015 Summer Solstice: 7th International Conference on Discrete Models of Complex Systems.
Taleghan, M.A. et al., 2015. PAC Optimal MDP Planning with Application to Invasive Species Management. Journal of Machine Learning Research, 16, pp.3877–3903. Available at: http://jmlr.org/papers/v16/taleghan15a.html.
2013
Houtman, R.M. et al., 2013. Allowing a wildfire to burn: Estimating the effect on future fire suppression costs. International Journal of Wildland Fire, 22(7), pp.871–882.
Poole, D. & Crowley, M., 2013. Cyclic causal models with discrete variables: Markov chain equilibrium semantics and sample ordering. In IJCAI International Joint Conference on Artificial Intelligence. Beijing, China, pp. 1060–1068. Available at: http://dl.acm.org/citation.cfm?id=2540281.
Dietterich, T.G., Taleghan, M.A. & Crowley, M., 2013. PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2013). Bellevue, WA, USA, p. 7. Available at: http://www.aaai.org/ocs/index.php/AAAI/AAAI13/paper/view/6478.
Crowley, M., 2013. Policy Gradient Optimization Using Equilibrium Policies for Spatial Planning Domains. In 13th INFORMS Computing Society Conference. Santa Fe, NM, United States.
2012
Hall, K. et al., 2012. Managing Invasive Species in a River Network. In Third International Conference on Computational Sustainability. Copenhagen, Denmark. Available at: http://www.cs.ubc.ca/ crowley/papers/compsust2012.pdf.
2011
Crowley, M., 2011. Equilibrium Policy Gradients for Spatiotemporal Planning. University of British Columbia. Available at: http://hdl.handle.net/2429/38971.
Crowley, M. & Poole, D., 2011. Policy gradient planning for environmental decision making with existing simulators. In Proceedings of the National Conference on Artificial Intelligence. San Francisco, pp. 1323–1330. Available at: http://www.scopus.com/inward/record.url?eid=2-s2.0-80055051332&partnerID=tZOtx3y1.
2010
Patitsas, E. et al., 2010. Circuits and logic in the lab : Toward a coherent picture of computation. In 15th Western Canadian Conference on Computing Education. Kelowna, BC, Canada. Available at: http://www.cs.ubc.ca/ crowley/papers/wccce2010.pdf.
2009
Crowley, M., Nelson, J. & Poole, D., 2009. Seeing the Forest Despite the Trees : Large Scale Spatial-Temporal Decision Making. In Conference on Uncertainty in Artificial Intelligence (UAI09). Montreal, Canada, pp. 126–134. Available at: http://www.cs.ubc.ca/ crowley/papers/uai09-mark-crowley.pdf.
2007
Crowley, M. et al., 2007. Adding Local Constraints to Bayesian Networks. In Advances in Artificial Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 344–355. Available at: http://www.springerlink.com/content/u1j205nhr750m717/.
2004
Crowley, M., 2004. Evaluating Influence Diagrams. Unpublished Working Paper.