Publications

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Author [ Title(Asc)] Type Year
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Crowley, M., 2021. Prediction and Causality: How Can Machine Learning be Used for COVID-19?. In "What Needs to be done in order to Curb the Spread of Covid-19: Exposure Notification, Legal Considerations, and Statistical Modeling", a Conference on Data and Privacy during a Global Pandemic. July. Waterloo, Canada: Master of Public Service (MPS) Policy and Data Lab, University of Waterloo, p. 6. Available at: https://uwaterloo.ca/master-of-public-service/events/data-and-privacy-during-global-pandemic-conference.
Crowley, M. & Poole, D., 2011. Policy gradient planning for environmental decision making with existing simulators. In 25th AAAI Conference on Artificial Intelligence (AAAI-11). San Francisco, pp. 1323–1330. Available at: https://www.scopus.com/record/display.uri?eid=2-s2.0-80055051332&origin=inward&txGid=de2006c39235aac9ba20cf0e76073dd9.
Crowley, M., 2013. Policy Gradient Optimization Using Equilibrium Policies for Spatial Planning Domains. In 13th INFORMS Computing Society Conference. Santa Fe, NM, United States.
Subramanian, S.Ganapathi et al., 2021. Partially Observable Mean Field Reinforcement Learning. In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS). 3–7 May. London, United Kingdom: International Foundation for Autonomous Agents and Multiagent Systems, pp. 537-545.
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.
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.
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Sikaroudi, M. et al., 2020. Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches. In International Conference on Intelligent Systems and Computer Vision (ISCV 2020) . Fez-Morrocco (virtual): IEEE, p. 8. Available at: https://arxiv.org/abs/2007.02200.
2007.02200.pdf
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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.
Sikaroudi, M. et al., 2021. Magnification Generalization for Histopathology Image Embedding. In IEEE International Symposium on Biomedical Imaging (ISBI). April. p. 5.
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Ghojogh, B., Karray, F. & Crowley, M., 2019. Locally Linear Image Structural Embedding for Image Structure Manifold Learning. In International Conference on Image Analysis and Recognition (ICIAR-19). Waterloo, Canada: Springer, Cham, pp. 126–138.
Ghojogh, B. & Crowley, M., 2019. Linear and Quadratic Discriminant Analysis: Tutorial. arXiv preprint arXiv:1906.02590.
Subramanian, S.Ganapthi, Bhalla, S. & Crowley, M., 2019. Learning Multi-Agent Communication with Reinforcement Learning. In Conference on Reinforcement Learning and Decision Making (RLDM-19). Montreal, Canada., p. 4.
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.
Subramanian_Crowley_-_2017_-_Learning_Forest_Wildfire_Dynamics_from_Satellite_Images_Using_Reinforcement_Learning.pdf
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Ma, H. et al., 2020. Isolation Mondrian Forest for Batch and Online Anomaly Detection. IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2020. Available at: arXiv preprint arXiv:2003.03692.
imondrian.pdf
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.
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.
Carrillo, J. & Crowley, M., 2019. Integration of Roadside Camera Images and Weather Data for monitoring Winter Road Surface Conditions. In Canadian Association of Road Safety Professionals CARSP Conference. CARSP Conference, Calgary, Alberta. , p. 4 (Won best paper award!). Available at: http://www.carsp.ca/research/research-papers/research-papers-search/download-info/integration-of-roadside-camera-images-and-weather-data-for-monitoring-winter-road-surface-conditions/.
Akgun, S.Alperen et al., 2021. Integrating Affective Expressions into the Search and Rescue Context in order to Improve Non-Verbal Human-Robot Interaction. In Workshop on Exploring Applications for Autonomous Non-Verbal Human-Robot Interactions (HRI). March. Virtual: ACM. Available at: https://sites.google.com/view/non-verbal-hri-2021/home.

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