This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 1Brown, Matthew R.G. (Psychiatry)
- 1Greiner, Russell (Computing Science)
- 1Heo, Giseon (Mathematical and Statistical Sciences; Denistry and Orthodontics)
- 1Miller, James (Electrical and Computer Engineering)
- 1Ray, Nilanjan (Computing Science)
- 1Schmuland, Byron (Mathematical and Statistical Sciences)
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Fall 2020
Organizational transactions generate immense amounts of data every day. The decisions made using such data are not only important for their financial impacts on the business; they also regulate the relationships with other businesses in their supply chain. There has been much research that...
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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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Dimensionality Reduction via the Johnson and Lindenstrauss Lemma: Mathematical and Computational Improvements
DownloadFall 2016
In an increasingly data-driven society, there is a growing need to simplify high-dimensional data sets. Over the course of the past three decades, the Johnson and Lindenstrauss (JL) lemma has evolved from a highly abstract mathematical result into a useful tool for dealing with data sets of...
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Spring 2017
At the core of many computer vision methods lies the question of how to represent data. Representing the data in a meaningful way, which highlights its most useful properties, can significantly affect the performance of any vision-based application. Traditional systems are heavily reliant on...