showcase

A selection of highlighted papers per year

Also see:

selected publications

2022

  1. IOTSMS
    Aggressive Driver Behavior Detection using Parallel Convolutional Neural Networks on Simulated and Real Driving Data
    Zehra Camlica, Jim Quesenberry, Daniel Carballo, and Mark Crowley
    In 9th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) IEEE, Milan, Italy, nov, 2022.
  2. Robot Rescue
    Using Affect as a Communication Modality to Improve Human-Robot Communication in Robot-Assisted Search and Rescue Scenarios
    Sami Alperen Akgun, Moojan Ghafurian, Mark Crowley, and Kerstin Dautenhahn.
    IEEE Transactions on Affective Computing. arXiv, nov, 2022.
  3. Mean Field MARL
    Decentralized Mean Field Games
    Sriram Ganapathi Subramanian, Matthew Taylor, Mark Crowley, and Pascal Poupart.
    In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2022) Virtual, feb, 2022.
  4. Multi-Advisor-QL
    Multi-Agent Advisor Q-Learning
    Journal of Artificial Intelligence Research (JAIR). 73, may, 2022.

2021

  1. MARLEmpircal
    Investigation of Independent Reinforcement Learning Algorithms in Multi-Agent Environments
    In NeurIPS 2021 Deep Reinforcement Learning Workshop dec, 2021.
  2. Acceleration of Large Margin Metric Learning for Nearest Neighbor Classification Using Triplet Mining and Stratified Sampling
    Parisa Poorheravi, Benyamin Ghojogh, Vincent Gaudet, Fakhri Karray, and Mark Crowley
    Journal of Computational Vision and Imaging Systems. 6, (1). jan, 2021.
  3. NLP-DigiPath
    Analysis of Language Embeddings for Classification of Unstructured Pathology Reports
    Aishwarya Krishna Allada, Yuanxin Wang, Veni Jindal, Morteza Babaie, H.R. Tizhoosh, and Mark Crowley
    In International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) IEEE, nov, 2021.
  4. PO-MFRL
    Partially Observable Mean Field Reinforcement Learning
    Sriram Ganapathi Subramanian, Matthew Taylor, Mark Crowley, and Pascal Poupart.
    In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS) International Foundation for Autonomous Agents and Multiagent Systems, London, United Kingdom, may, 2021.
  5. Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem
    Milad Sikaroudi, Benyamin Ghojogh, Fakhri Karray, Mark Crowley, and H. R. Tizhoosh.
    In 25th International Conference on Pattern Recognition (ICPR) IEEE, Milan, Italy (virtual), jan, 2021.
  6. Amrl
    Active Measure Reinforcement Learning for Observation Cost Minimization: A framework for minimizing measurement costs in reinforcement learning
    Colin Bellinger, Rory Coles, Mark Crowley, and Isaac Tamblyn.
    In Canadian Conference on Artificial Intelligence Springer, 2021.
  7. Recognition of a Robot’s Affective Expressions under Conditions with Limited Visibility
    Moojan Ghafurian, Sami Alperen Akgun, Mark Crowley, and Kerstin Dautenhahn.
    In 18th International Conference promoted by the IFIP Technical Committee 13 on Human–Computer Interaction (INTERACT 2021) Bari, Italy, sep, 2021.
  8. patent
    Multi-Level Collaborative Control System With Dual Neural Network Planning For Autonomous Vehicle Control In A Noisy Environment
    Zhiyuan Du, Joseph Lull, Rajesh Malhan, Sriram Ganapathi Subramanian, Sushrut Bhalla, Jaspreet Sambee, Mark Crowley, Sebastian Fischmeister, Donghyun Shin, William Melek, Baris Fidan, Ami Woo, and Bismaya Sahoo.
    US Patent Office: #US 11,131,992 B2. sep, 2021.
  9. QQE
    Quantile–Quantile Embedding for distribution transformation and manifold embedding with ability to choose the embedding distribution
    Benyamin Ghojogh, Fakhri Karray, and Mark Crowley
    Machine Learning with Applications (MLWA). 6, 2021.

2020

  1. Multi Type Mean Field Reinforcement Learning
    Sriram Ganapathi Subramanian, Pascal Poupart, Matthew Taylor, and Nidhi Hegde.
    In Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS) International Foundation for Autonomous Agents and Multiagent Systems, London, United Kingdom, 2020.
  2. iMondrian
    Isolation Mondrian Forest for Batch and Online Anomaly Detection
    Haoran Ma, Benyamin Ghojogh, Maria N Samad, Dongyu Zheng, and Mark Crowley
    In IEEE International Conference on Systems, Man, and Cybernetics (IEEE-SMC-2020) IEEE SMC, Toronto, Canada (virtual), oct, 2020.
  3. WildfireMLRev
    A review of machine learning applications in wildfire science and management
    Piyush Jain, Sean CP Coogan, Sriram Ganapathi Subramanian, Mark Crowley, Steve Taylor, and Mike D Flannigan.
    Environmental Reviews. 28, (3). Canadian Science Publishing, jul, 2020.
  4. Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study
    Milad Sikaroudi, Amir Safarpoor, Benyamin Ghojogh, Sobhan Shafiei, Mark Crowley, and HR Tizhoosh.
    In International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’20) Montreal, Quebec, Canada (virtual), jul, 2020.
  5. Distributed Nonlinear Model Predictive Control and Metric Learning for Heterogeneous Vehicle Platooning with Cut-in/Cut-out Maneuvers
    Mohammad Hossein Basiri, Benyamin Ghojogh, Nasser L Azad, Sebastian Fischmeister, Fakhri Karray, and Mark Crowley
    In Proceeding of the 59th IEEE Conference on Decision and Control (CDC-2020) Jeju Island, Korea (virtual), dec, 2020.

2019

  1. Semantic Workflows and Machine Learning for the Assessment of Carbon Storage by Urban Trees
    Juan Carrillo, Daniel Garijo, Mark Crowley, Yolanda Gil, and Katherine Borda.
    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, 2019.
  2. Instance Ranking and Numerosity Reduction Using Matrix Decompositionand Subspace Learning
    Benyamin Ghojogh, and Mark Crowley
    In Canadian Conference on Artificial Intelligence Springer’s Lecture Notes in Artificial Intelligence., Kingston, ON, Canada, 2019.
  3. Principal Component Analysis Using Structural Similarity Index for Images
    Benyamin Ghojogh, Fakhri Karray, and Mark Crowley
    In International Conference on Image Analysis and Recognition (ICIAR-19) Waterloo, Canada, 2019.

2018

  1. MCTS+A3C
    Combining MCTS and A3C for prediction of spatially spreading processes in forest wildfire settings
    Sriram Ganapathi Subramanian, and Mark Crowley
    In Canadian Conference on Artificial Intelligence Toronto, Ontario, Canada, 2018.
  2. Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models From Satellite Images
    Sriram Ganapathi Subramanian, and Mark Crowley
    Frontiers in ICT. 5, (6). Frontiers, apr, 2018.

2017

  1. Learning Forest Wildfire Dynamics from Satellite Images Using Reinforcement Learning
    Sriram Ganapathi Subramanian, and Mark Crowley
    In Conference on Reinforcement Learning and Decision Making Ann Arbor, MI, USA., 2017.
  2. AI Education Through Real World Problems
    markcrowley.
    In The Seventh Symposium on Educational Advances in Artificial Intellgience. San Francisco, USA., 2017.

2016

  1. Anomaly Detection Using Inter-Arrival Curves for Real-time Systems
    Mahmoud Salem, Mark Crowley, and Sebastian Fischmeister.
    In 2016 28th Euromicro Conference on Real-Time Systems Toulouse, France, jul, 2016.

2015

  1. PAC Optimal MDP Planning with Application to Invasive Species Management
    Majid Alkaee Taleghan, Thomas G. Dietterich, Mark Crowley, Kim Hall, and H. Jo Albers.
    Journal of Machine Learning Research. 16, 2015.

2014

  1. Using equilibrium policy gradients for spatiotemporal planning in forest ecosystem management
    markcrowley.
    IEEE Transactions on Computers. 63, (1). IEEE computer Society Digital Library. IEEE Computer Society., 2014.

2013

  1. Allowing a wildfire to burn: Estimating the effect on future fire suppression costs
    Rachel M. Houtman, Claire A. Montgomery, Aaron R. Gagnon, David E. Calkin, Thomas G. Dietterich, Sean McGregor, and Mark Crowley
    International Journal of Wildland Fire. 22, (7). 2013.
  2. PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs
    Thomas G Dietterich, Majid Alkaee Taleghan, and Mark Crowley
    In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2013) Bellevue, WA, USA, 2013.
  3. Cyclic causal models with discrete variables: Markov chain equilibrium semantics and sample ordering
    David Poole, and Mark Crowley
    In IJCAI International Joint Conference on Artificial Intelligence Beijing, China, 2013.