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- 26Artificial Intelligence
- 23Reinforcement Learning
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- 165Graduate and Postdoctoral Studies (GPS), Faculty of
- 165Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 8Computing Science, Department of
- 7Computing Science, Department of/Technical Reports (Computing Science)
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- 165Thesis
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Fall 2024
It has been shown that pretrained language models exhibit biases and social stereotypes. Prior work on debiasing these language models has largely focussed on modifying embedding spaces in pretraining, which is not scalable for large models. Since pretrained models are typically fine-tuned on...
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Deep Learning-based Forecasting and Energy Management Algorithms for Smart Grid Applications
DownloadFall 2023
With the increasing global problems concerning energy security and climate change, new challenges in social progress and human survival have come to the fore. Requiring no fuel, and being renewable and non-polluting, renewable energy (RE) resources, typically from photovoltaic and wind sources,...
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Fall 2011
The imbalanced learning problem occurs in a large number of economic and health domains of great importance; consequently, it has drawn a significant amount of interest from academia, industry, and government funding agencies. Several researchers have used stratification to alleviate this...
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Development and Evaluation of Interpretable Machine Learning Models for Mitigating Winter Road Safety – An Empirical Investigation
DownloadFall 2024
In Canada, winter crashes account for a significant portion of crashes each year. This thesis investigates the utility of machine learning (ML) for understanding and mitigating winter road risks. Despite their potential to achieve high predictive performance in the face of complex data...
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Development of AI-based ergonomics risk assessment tools for harmonization of industrial work systems
DownloadFall 2023
Manufacturing industry workers face significant ergonomic risks due to poorly designed work systems. Consequently, it is crucial to periodically assess work systems to identify areas for improvement. However, the assessment process is often disregarded due to the absence of userfriendly...
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Fall 2012
Functional Magnetic Resonance Imaging (fMRI) measures the dynamic activity of each voxel of a brain. This dissertation addresses the challenge of learning a diagnostic classifier that uses a subject’s fMRI data to distinguish subjects with neuropsychiatric disorders from healthy controls. fMRI...
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Fall 2023
The problem of missing data is omnipresent in a wide range of real-world datasets. When learning and predicting on this data with neural networks, the typical strategy is to fill-in or complete these missing values in the dataset, called impute-then-regress. Much less common is to attempt to...
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Spring 2019
In this thesis we introduce a new loss for regression, the Histogram Loss. There is some evidence that, in the problem of sequential decision making, estimating the full distribution of return offers a considerable gain in performance, even though only the mean of that distribution is used in...
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Fall 2019
Artificial agents have been shown to learn to communicate when needed to complete a cooperative task. Some level of language structure (e.g., compositionality) has been found in the learned communication protocols. This observed structure is often the result of specific environmental pressures...