Publications
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.
, 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.
, 2019. Generative locally linear embedding: A module for manifold unfolding and visualization. Software Impacts, 9, p.3.
, 2021. 2021-softimp-ghojogh-generative.pdfGenerative Locally Linear Embedding. Available at: https://arxiv.org/abs/2104.01525.
, 2021. 2021-smc-ghojogh-generative_locally_linear_embedding.pdfGeneralized 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.
, 2020. Fitting A Mixture Distribution to Data: Tutorial. ArXiv preprint. arXiv:1901.06708.
, 2019. Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks. In IEEE International Joint Conference on Neural Networks (IJCNN). Glasgow, UK: IEEE.
, 2020. Fisher and kernel fisher discriminant analysis: Tutorial. arXiv preprint arXiv:1906.09436.
, 2019. Feature selection and feature extraction in pattern analysis: A literature review. arXiv preprint arXiv:1905.02845.
, 2019. Evaluating Influence Diagrams. Unpublished Working Paper.
, 2004. Equilibrium Policy Gradients for Spatiotemporal Planning. University of British Columbia. Available at: http://hdl.handle.net/2429/38971.
, 2011. Eigenvalue and Generalized Eigenvalue Problems: Tutorial. ArXiv Preprint arXiv:1903.11240.
, 2019. Distributed Voting in Beep Model. arXiv preprint arXiv:1910.09882.
, 2019. Distributed Nonlinear Model Predictive Control and Metric Learning for Heterogeneous Vehicle Platooning with Cut-in/Cut-out Maneuvers. 59th IEEE Conference on Decision and Control (CDC) 2020. Available at: arXiv preprint arXiv:2004.00417.
, 2020. Deep Multi Agent Reinforcement Learning for Autonomous Driving. In Canadian Conference on Artificial Intelligence. Spring, Lecture Notes in Artificial Intelligence, p. 17.
, 2020. deep_multi_agent_reinforcement_learning_for_autonomous_driving-full.pdfDecision 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.
, 2018. SelfDrivingAssist_3.pdfCyclic 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.
, 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.
, 2013. Comparison of Deep Learning models for Determining Road Surface Condition from Roadside Camera Images and Weather Data. In TAC-ITS Canada Joint Conference. Halifax, Canada, p. 17. Available at: https://tac-its.ca/conference-papers/comparison-deep-learning-models-determining-road-surface-condition-roadside-camera.
, 2019.