Publications
] , 2019. Unsupervised and supervised principal component analysis: Tutorial. arXiv preprint arXiv:1906.03148.
, 2019. The theory behind overfitting, cross validation, regularization, bagging, and boosting: tutorial. arXiv preprint arXiv:1905.12787.
, 2019. Quantized Fisher Discriminant Analysis. arXiv preprint arXiv:1909.03037.
, 2019. Linear and Quadratic Discriminant Analysis: Tutorial. arXiv preprint arXiv:1906.02590.
, 2019. 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. Distributed Voting in Beep Model. arXiv preprint arXiv:1910.09882.
, 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.
, 2019. Eigenvalue and Generalized Eigenvalue Problems: Tutorial. ArXiv Preprint arXiv:1903.11240.
, 2019. Addressing the Mystery of Population Decline of the Rose-Crested Blue Pipit in a Nature Preserve using Data Visualization. ArXiv Preprint. ArXiv: 1903.06671.
, 2018. Principal Sample Analysis for Data Reduction. In International Conference on Big Knowledge (ICBK) . Singapore: IEEE, 2018.
PSA_Ghojogh_Crowley_2018.pdf, 2021. Recognition of a Robot's Affective Expressions under Conditions with Limited Visibility. In 18th International Conference promoted by the IFIP Technical Committee 13 on Human–Computer Interaction (INTERACT 2021). September. Bari, Italy, p. 22.
, 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, 2018. Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program. AI Matters, 3, pp.23–31. Available at: http://doi.acm.org/10.1145/3175502.3175509.
blueskyideasoneaai.pdf, 2020. Multi-Level Collaborative Control System With Dual Neural Network Planning For Autonomous Vehicle Control In A Noisy Environment. , US11131992B2(US Patent Office). Available at: https://patents.google.com/patent/US11131992B2/en.
patent-design.png, 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.
, 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.
, 2015. Answering Simple Questions About Spatially Spreading Systems. In 2015 Summer Solstice: 7th International Conference on Discrete Models of Complex Systems.
, 2014. Using equilibrium policy gradients for spatiotemporal planning in forest ecosystem management. IEEE Transactions on Computers, 63(1), pp.142–154. Available at: http://doi.ieeecomputersociety.org/10.1109/TC.2013.113.
, 2013. Policy Gradient Optimization Using Equilibrium Policies for Spatial Planning Domains. In 13th INFORMS Computing Society Conference. Santa Fe, NM, United States.
