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- 22Artificial Intelligence
- 18Reinforcement Learning
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- 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
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- 144Thesis
- 8Report
- 4Article (Published)
- 1Article (Draft / Submitted)
- 1Conference/Workshop Poster
- 1Conference/Workshop Presentation
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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 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...
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Enhancing the Architecture of Context-Aware Driver Assistance Systems by Incorporating Insights from Naturalistic Driving Data
DownloadSpring 2019
Driving assistance systems (DASs) have received a great deal of attention in the past decades as an active and effective collision countermeasure. DASs potential benefits will be attained by enhancing the systems’ awareness regarding the dynamic driving context including the change in the driver...
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Estimating Instantaneous Fuel Consumption of Vehicles By Using Machine Learning And Real-Time On-Board Diagnostics (OBD) Data
Download2022-06-01
Ansari, Amir, Abediasl, Hamidreza, Patel, Parth Rakeshkumar, Hosseini, Vahid, Koch, Charles Robert, Shahbakhti, Mahdi
Estimation of instantaneous fuel consumption of fleet vehicles to identify the causes of high fuel consumption and determine the optimum vehicle type for different applications and driving cycles is essential for the design of an intelligent fleet management system. Developing a practical and...
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Estimating the Overlap of Top Instances in Lists Ranked by Correlation to Label
Spring 2012
Recent advances in high-throughput technologies, such as genome-wide SNP analysis and microar- ray gene expression profiling, have led to a multitude of ranked lists, where the features (SNPs, genes) are sorted based on their individual correlation with a phenotype. Multiple reviews have shown...