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- 22Artificial Intelligence
- 19Reinforcement Learning
- 16Deep Learning
- 10Computer Vision
- 10Natural Language Processing
- 144Graduate and Postdoctoral Studies (GPS), Faculty of
- 144Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 8Computing Science, Department of
- 7Computing Science, Department of/Technical Reports (Computing Science)
- 2Chemical and Materials Engineering, Department of
- 2Biological Sciences, Department of
- 144Thesis
- 8Report
- 4Article (Published)
- 2Conference/Workshop Poster
- 1Article (Draft / Submitted)
- 1Conference/Workshop Presentation
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2012
Bowling, Michael, Zinkevich, Martin
Online learning aims to perform nearly as well as the best hypothesis in hindsight. For some hypothesis classes, though, even finding the best hypothesis offline is challenging. In such offline cases, local search techniques are often employed and only local optimality guaranteed. For online...
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2022-01-01
Xiunan Wang, Hao Wang, Pouria Ramazi, Kyeongah Nah, Mark Lewis
Accurate prediction of the number of daily or weekly confirmed cases of COVID-19 is critical to the control of the pandemic. Existing mechanistic models nicely capture the disease dynamics. However, to forecast the future, they require the transmission rate to be known, limiting their prediction...
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2011
Technical report TR11-01. Causality is a fundamental concept in reasoning. The effectiveness of many reasoning tasks depends on the understanding of the underlying cause-effect relationships. Therefore, the notion of causality has been explored in a wide range of disciplines. Causal discovery,...
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2022-03-10
Xiunan Wang, Hao Wang, Pouria Ramazi, Kyeongah Nah, Mark Lewis
Accurate prediction of the number of daily or weekly confirmed cases of COVID-19 is critical to the control of the pandemic. Existing mechanistic models nicely capture the disease dynamics. However, to forecast the future, they require the transmission rate to be known, limiting their prediction...
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Automated semantic segmentation of NiCrBSi-WC optical microscopy images using convolutional neural networks
Download2022-01-01
Rose, D., Forth, J., Henein, H., Wolfe, T., Qureshi, A.
Convolutional neural networks (CNNs) were used for the semantic segmentation of angular monocrystalline WC from NiCrBSi-WC optical microscopy images. This deep learning approach was able to emulate the laborious task of manual segmentation effectively, with a mean intersection over union (IOU)...
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A Hierarchical Constrained Reinforcement Learning for Optimization of Bitumen Recovery Rate in a Primary Separation Vessel
Download2020-01-01
Shafi, Hareem, Velswamy, Kirubakaran, Ibrahim, Fadi, Huang,Biao
This work proposes a two-level hierarchical constrained control structure for reinforcement learning (RL) with application in a Primary Separation Vessel (PSV). The lower level is concerned with servo tracking and regulation of the interface level against variances in ore quality by manipulating...
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2006
Poulin, Brett, Wan, Xiang, Kolacz, Tom
Technical report TR06-03. Single nucleotide polymorphisms (SNPs) are genetic markers that may be used to identify the causes and risks of cancer. The sheer volume of data generated by SNP studies is difficult to analyze by hand. Machine learning techniques have been developed to address the types...