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
- 2Abdi Oskouie, Mina
- 2Birkbeck, Neil Aylon Charles
- 2Cai, Zhipeng
- 2Chen, Jiyang
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 74Machine Learning
- 70Reinforcement Learning
- 41Artificial Intelligence
- 36Machine learning
- 22Natural Language Processing
- 22Reinforcement learning
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On Policy Decisions of Polymorphic Inline Caches in Dynamically-Typed Language Implementations
DownloadFall 2023
Dynamically-typed languages running on Virtual Machines (VMs) are commonly used, but the lack of explicit type information poses a challenge to producing efficient code. In general, without type annotations, it is impossible to statically infer an object's type to determine which methods to...
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Fall 2012
Selecting appropriate rehabilitation treatments for injured workers has been a challenging task for clinicians and health care funders. Currently, clinicians are unable to identify the optimal treatment for a patient with absolute confidence and are looking for assistance from other research...
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Spring 2024
In machine learning, sparse neural networks provide higher computational efficiency and in some cases, can perform just as well as fully-connected networks. In the online and incremental reinforcement learning (RL) problem, Prediction Adapted Networks (Martin and Modayil, 2021) is an algorithm...