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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Fall 2011
This thesis studies the reinforcement learning and planning problems that are modeled by a discounted Markov Decision Process (MDP) with a large state space and finite action space. We follow the value-based approach in which a function approximator is used to estimate the optimal value function....
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Spring 2015
This dissertation explores regularized factor models as a simple unification of machine learn- ing problems, with a focus on algorithmic development within this known formalism. The main contributions are (1) the development of generic, efficient algorithms for a subclass of regularized...
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Spring 2021
On July 20, 1969, the Apollo 11 lunar module, with Astronauts Neil Armstrong and Buzz Aldrin aboard, landed on the moon. It was a great achievement in space exploration. Most people know of this mission's success; yet, there is an untold story about this mission that many people are not aware...
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Fall 2009
Learning and planning are two fundamental problems in artificial intelligence. The learning problem can be tackled by reinforcement learning methods, such as temporal-difference learning, which update a value function from real experience, and use function approximation to generalise across...
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Spring 2024
This dissertation develops simple and practical learning algorithms from first principles for long-lived agents. Formally, the algorithms are developed within the reinforcement learning framework for continuing (non-episodic) problems, in which the agent-environment interaction goes on ad...
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Spring 2018
Recent advancements in reinforcement learning have made the field interesting to academia and industry alike. Many of these advancements depend on deep learning as a means to approximate a value function or a policy. This dependency usually relies on high performance hardware (e.g., a graphics...
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Fall 2022
While traditional machine learning algorithms learn to solve a task directly, meta- learning aims to learn about and improve another learning algorithm’s performance. However, existing meta-learning methods either only work with differentiable algo- rithms or are handcrafted to improve a specific...
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Spring 2017
Information extraction, extracting structured information from text, is a vital component for many natural language tasks such as question answering. It generally consists of two components: (1) named entity recognition (NER), identifying noun phrases that are names of organizations, persons, or...