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- 22Artificial Intelligence
- 18Reinforcement Learning
- 16Deep 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
- 2Biological Sciences, Department of
- 144Thesis
- 8Report
- 4Article (Published)
- 1Article (Draft / Submitted)
- 1Conference/Workshop Poster
- 1Conference/Workshop Presentation
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Spring 2019
The extraction of knowledge from data is a relatively recent computational pursuit which has been the focus of significant research attention and has an extensive field of potential applications. With the advent of widespread data collection describing a variety of systems spanning many fields of...
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Spring 2016
Computer aided diagnosis of mental disorders like Attention Deficit Hyperactivity Disorder (ADHD) and Autism is a primary step towards automated detection and prognosis of these psychiatric diseases. This dissertation applies analyses based on learning models that use structural texture and...
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Spring 2023
Gradient Descent algorithms suffer many problems when learning representations using fixed neural network architectures, such as reduced plasticity on non-stationary continual tasks and difficulty training sparse architectures from scratch. A common workaround is continuously adapting the neural...
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Fall 2019
Improvisation is a form of live theatre where artists perform real-time, dynamic problem solving to collaboratively generate interesting narratives. The main contribution of this thesis is the development of artificial improvisation: improvised theatre performed by humans alongside intelligent...
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Fall 2017
Modern board, card, and video games are challenging domains for AI research due to their complex game mechanics and large state and action spaces. For instance, in Hearthstone — a popular collectible card (CC) (video) game developed by Blizzard Entertainment — two players first construct their...
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Fall 2022
Convolution Neural Networks (CNNs) have rapidly evolved since their neuroscience beginnings. These models efficiently and accurately classify images by optimizing the model’s hidden representations to these images through training. These representa- tions have been shown to resemble neural data...
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Fall 2021
With the advent of cloud computing, many organizations are moving their software systems to cloud environments. This migration from on-premises to cloud infrastructure has led to the emergence of cloud applications. One of the essential concepts around cloud applications and cloud services is...
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Improving the reliability of reinforcement learning algorithms through biconjugate Bellman errors
DownloadSpring 2024
In this thesis, we seek to improve the reliability of reinforcement learning algorithms for nonlinear function approximation. Semi-gradient temporal difference (TD) update rules form the basis of most state-of-the-art value function learning systems despite clear counterexamples proving their...
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In-silico Methods for Drug Discovery: Applications of Molecular Dynamics, Drug Docking, and Machine Learning
DownloadSpring 2024
Drug discovery is a venture that is costly in both time and money. In-silico methods are a core part of biomedical research, from traditional tools such as drug docking and molecular dynamics to newer machine learning frameworks, all of which are more efficient in both time and cost compared to...
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Insights into Early Word Comprehension - Tracking the Neural Representations of Word Semantics in Infants
DownloadSpring 2022
Infants start developing rudimentary language skills and can start understanding simple words well before their first birthday. This development has also been shown primarily using Event Related Potential (ERP) techniques to find evidence of word comprehension in the infant brain. While these...