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Mark Crowley
Mark Crowley
Associate Professor, Electrical and Computer Engineering, University of Waterloo, Waterloo
Dirección de correo verificada de uwaterloo.ca - Página principal
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A review of machine learning applications in wildfire science and management.
SCP Coogan, P Jain, S Ganapathi Subramanian, S Taylor, M Crowley, ...
Environmental Reviews 28 (4), 2020
6242020
The theory behind overfitting, cross validation, regularization, bagging, and boosting: tutorial
B Ghojogh, M Crowley
arXiv preprint arXiv:1905.12787, 2019
3032019
Feature selection and feature extraction in pattern analysis: A literature review
B Ghojogh, MN Samad, SA Mashhadi, T Kapoor, W Ali, F Karray, ...
arXiv preprint arXiv:1905.02845, 2019
1602019
Eigenvalue and generalized eigenvalue problems: Tutorial
B Ghojogh, F Karray, M Crowley
arXiv preprint arXiv:1903.11240, 2019
1572019
Linear and quadratic discriminant analysis: Tutorial
B Ghojogh, M Crowley
arXiv preprint arXiv:1906.02590, 2019
1562019
Allowing a wildfire to burn: Estimating the effect on future fire suppression costs
R Houtman, C Montgomery, A Gagnon, D Calkin, T Dietterich, ...
International Journal of Wildland Fire, 2013
1152013
Deep multi agent reinforcement learning for autonomous driving
S Bhalla
University of Waterloo, 2020
692020
Elements of dimensionality reduction and manifold learning
B Ghojogh, M Crowley, F Karray, A Ghodsi
Springer, 2023
632023
Using spatial reinforcement learning to build forest wildfire dynamics models from satellite images
S Ganapathi Subramanian, M Crowley
Frontiers in ICT 5, 6, 2018
632018
Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program
E Eaton, S Koenig, C Schulz, F Maurelli, J Lee, J Eckroth, M Crowley, ...
AI Matters 3 (4), 23-31, 2017
622017
Multidimensional Scaling, Sammon Mapping, and Isomap
B Ghojogh, M Crowley, F Karray, A Ghodsi
Elements of Dimensionality Reduction and Manifold Learning, 185-205, 2023
572023
KKT conditions, first-order and second-order optimization, and distributed optimization: tutorial and survey
B Ghojogh, A Ghodsi, F Karray, M Crowley
arXiv preprint arXiv:2110.01858, 2021
452021
The Theory Behind Overfitting
B Ghojogh, M Crowley
Cross Validation, Regularization, Bagging, and Boosting: Tutorial. arXiv 1905, 2019
452019
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks
B Ghojogh, M Sikaroudi, S Shafiei, HR Tizhoosh, F Karray, M Crowley
arXiv preprint arXiv:2004.04674, 2020
432020
Fitting a mixture distribution to data: tutorial
B Ghojogh, A Ghojogh, M Crowley, F Karray
arXiv preprint arXiv:1901.06708, 2019
412019
Isolation Mondrian forest for batch and online anomaly detection
H Ma, B Ghojogh, MN Samad, D Zheng, M Crowley
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020
382020
Anomaly detection using inter-arrival curves for real-time systems
M Salem, M Crowley, S Fischmeister
2016 28th Euromicro Conference on Real-Time Systems (ECRTS), 97-106, 2016
382016
Uniform manifold approximation and projection (UMAP) and its variants: tutorial and survey
B Ghojogh, A Ghodsi, F Karray, M Crowley
arXiv preprint arXiv:2109.02508, 2021
372021
Distributed nonlinear model predictive control and metric learning for heterogeneous vehicle platooning with cut-in/cut-out maneuvers
MH Basiri, B Ghojogh, NL Azad, S Fischmeister, F Karray, M Crowley
2020 59th IEEE Conference on Decision and Control (CDC), 2849-2856, 2020
372020
Generative adversarial networks and adversarial autoencoders: Tutorial and survey
B Ghojogh, A Ghodsi, F Karray, M Crowley
arXiv preprint arXiv:2111.13282, 2021
332021
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20