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A Universal Approximation Theorem for Tychonoff Spaces with Application to Spaces of Probability and Finite Measures
DownloadFall 2022
Universal approximation refers to the property of a collection of functions to approximate continuous functions. Past literature has demonstrated that neural networks are dense in continuous functions on compact subsets of finite-dimensional spaces, and this document extends those findings to...
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Fall 2012
Processing of oil sands ores to extract bitumen generates large volumes of tailings which are deposited into large settling basins, where the solids settle by gravity over 3-4 years to become mature fine tailings (MFT). Methanogenesis has been correlated with increased water recovery from and...
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Action Selection for Hammer Shots in Curling: Optimization of Non-convex Continuous Actions With Stochastic Action Outcomes
DownloadSpring 2017
Optimal decision making in the face of uncertainty is an active area of research in artificial intelligence. In this thesis, I present the sport of curling as a novel application domain for research in optimal decision making. I focus on one aspect of the sport, the hammer shot, the last shot...
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Spring 2021
Learning about many things can provide numerous benefits to a reinforcement learning system. For example, learning many auxiliary value functions, in addition to optimizing the environmental reward, appears to improve both exploration and representation learning. The question we tackle in this...
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Spring 2016
Monte Carlo methods are a simple, effective, and widely deployed way of approximating integrals that prove too challenging for deterministic approaches. This thesis presents a number of contributions to the field of adaptive Monte Carlo methods. That is, approaches that automatically adjust the...
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Spring 2024
In model-based reinforcement learning, an agent can improve its policy by planning: learning from experience generated by a model. Search control is the problem of determining which starting state should be used to generate this experience. Given a limited planning budget, an agent should be...
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Addressing the Challenges of Applying Machine Learning for Predicting Mental Disorders and Their Prognosis Using Two Case Studies
DownloadSpring 2019
Ghoreishiamiri, Seyedehreyhaneh
One of the principal applications of machine learning in psychiatry is to build automated tools that can help clinicians predict the diagnosis and prognosis of mental disorders using available data from patients’ profiles. Here, in two different studies, we investigate ways to use machine learn-...
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Fall 2017
High pressure carbon dioxide adsorption processes are employed in applications such as carbon dioxide capture and supercritical fluid chromatography (SFC). Carbon dioxide capture using adsorption has gained wide attention because of the promising materials that are developed for this application....
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Advanced quantitative techniques to enhance heavy and civil construction information modeling
DownloadSpring 2011
Site development in heavy and civil construction need to consider many rules such as ensuring proper drainage, prevention of flood, safety driving, optimizing earthwork, minimizing fleet travel distances, proper fleet matching and achieving high equipment utilization rates. In recent decades,...
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Spring 2021
Smart grid, typically regarded as the next generation of electrical power grid, can bring numerous benefits for electric utilities and customers with substantial economic and ecological benefits. However, uncertainties caused by the distributed power generation from renewable energy sources,...