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Author Title [ Type(Asc)] Year
Conference Paper
Ghojogh, B. et al., 2020. Weighted Fisher Discriminant Analysisin the Input and Feature Spaces. In International Conference on Image Analysis and Recognition (ICIAR). Póvoa de Varzim, Portugal (virtual): Springer.
Ghojogh, B., Karray, F. & Crowley, M., 2020. Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders. In International Conference on Image Analysis and Recognition. Póvoa de Varzim, Portugal (virtual): Springer.
Ghojogh, B., Karray, F. & Crowley, M., 2020. Generalized Subspace Learning by Roweis Discriminant Analysis. In International Conference on Image Analysis and Recognition. Póvoa de Varzim, Portugal (virtual): Springer. Available at: http://arxiv.org/abs/1910.05437.
Ghojogh, B. et al., 2020. Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks. In IEEE International Joint Conference on Neural Networks (IJCNN). Glasgow, UK: IEEE.
Ghojogh, B., Karray, F. & Crowley, M., 2020. Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces. In International Conference on Image Analysis and Recognition. Póvoa de Varzim, Portugal (virtual): Springer.
Ghojogh, B., Karray, F. & Crowley, M., 2020. Anomaly Detection and Prototype Selection Using Polyhedron Curvature. In Canadian Conference on Artificial Intelligence. Ottawa, Canada: Springer, p. 10.
Bhalla, S., Subramanian, S.Ganapathi & Crowley, M., 2020. Deep Multi Agent Reinforcement Learning for Autonomous Driving. In Canadian Conference on Artificial Intelligence. Spring, Lecture Notes in Artificial Intelligence, p. 17.
deep_multi_agent_reinforcement_learning_for_autonomous_driving-full.pdf
Ghojogh, B., Karray, F. & Crowley, M., 2019. Principal Component Analysis Using Structural Similarity Index for Images. In International Conference on Image Analysis and Recognition (ICIAR-19). Waterloo, Canada: Springer, Cham, pp. 77–88.
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., Karray, F. & Crowley, M., 2019. Image Structure Subspace Learning Using Structural Similarity Index. In International Conference on Image Analysis and Recognition (ICIAR-19). Waterloo, Canada: Springer, Cham, pp. 33–44.
Garcia, J.Manuel Car 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 (SciKnow19). Los Angeles, California, USA, pp. 1–6. Available at: https://www.semanticscholar.org/paper/Semantic-Workflows-and-Machine-Learning-for-the-of-Garcia-Garijo/cb059bd7de50122a9a7b5a778e04e21f2c02b2c6.
9bd7de50122a9a7b5a778e04e21f2c02b2c6.pdf
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.
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
Subramanian, S.Ganapathi & Crowley, M., 2018. Combining MCTS and A3C for prediction of spatially spreading processes in forest wildfire settings. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Toronto, Ontario, Canada, pp. 285–291.

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