Publications

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Author Title [ Type(Desc)] Year
Conference Paper
Carrillo, J. et al., 2019. Semantic Workflows and Machine Learning for the Assessment of Carbon Storage by Urban Trees. In Third International Workshop on Capturing Scientific Knowledge (Sciknow 2019), Collocated with the tenth International Conference on Knowledge Capture (K-CAP). Los Angeles, California, USA, p. 6.
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.
Carrillo, J. et al., 2019. Comparison of Deep Learning models for Determining Road Surface Condition from Roadside Camera Images and Weather Data. In The Transportation Association of Canada and Intelligent Transportation Systems Canada Joint Conference (TAC-ITS). Halifax, Canada, p. 16.
Bhalla, S. et al., 2019. Compact Representation of a Multi-dimensional Combustion Manifold Using Deep Neural Networks. In European Conference on Machine Learning. Wurzburg, Germany, p. 8.
screen_shot_2019-07-21_at_3.26.52_pm.png ecml_combustion_ml.pdf
Ghojogh, B. & Crowley, M., 2019. Instance Ranking and Numerosity Reduction Using Matrix Decompositionand Subspace Learning. In Canadian Conference on Artificial Intelligence. Kingston, ON, Canada: Springer’s Lecture Notes in Artificial Intelligence., p. 12.
Bhalla, S., Subramanian, S.G. & Crowley, M., 2019. Training Cooperative Agents for Multi-Agent Reinforcement Learning. In Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019). Montreal, Canada.
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/.
NekoeiQachkanloo, H. et al., 2019. Artificial Counselor System For Stock Investment. In Innovative Applications of Artificial Intelligence (IAAI-19). 27 January . IAAI-19 Conference, Honolulu, Hawaii, USA, 2019.: AAAI Press., p. 8. Available at: https://aaai.org/ojs/index.php/AAAI/article/view/5016.
StockInvestPaper_Final.pdf
Ghojogh, B. & Crowley, M., 2018. Principal Sample Analysis for Data Reduction. In International Conference on Big Knowledge (ICBK) . Singapore: IEEE, 2018.
PSA_Ghojogh_Crowley_2018.pdf
Subramanian, S.G. & Crowley, M., 2018. Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Settings. In Canadian Conference on Artificial Intelligence. Toronto, Ontario, Canada: Springer, pp. 285-291. Available at: https://link.springer.com/chapter/10.1007/978-3-319-89656-4_28.
Canadian_AI_forestfire_2.pdf
Subramanian, S.G. et al., 2018. Decision Assist For Self-Driving Cars. In 31st Canadian Conference on Artificial Intelligence, Candian AI 2018. Toronto, Ontario, Canada: Springer, pp. 381-387. Available at: https://link.springer.com/chapter/10.1007%2F978-3-319-89656-4_44.
SelfDrivingAssist_3.pdf
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
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.
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.
Crowley, M., 2015. Answering Simple Questions About Spatially Spreading Systems. In 2015 Summer Solstice: 7th International Conference on Discrete Models of Complex Systems.
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.
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.

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