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Skip to Search Results- 184Machine Learning
- 26Artificial Intelligence
- 23Reinforcement Learning
- 21Deep Learning
- 11Natural Language Processing
- 10Computer Vision
- 165Graduate and Postdoctoral Studies (GPS), Faculty of
- 165Graduate 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
- 165Thesis
- 8Report
- 5Article (Published)
- 2Conference/Workshop Poster
- 2Research Material
- 1Article (Draft / Submitted)
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2003
Greiner, Russell, Wishart, David, Eisner, Roman, Lu, Z., Lu, Paul, Macdonell, Cam, Poulin, B., Szafron, Duane, Anvik, J.
Technical report TR03-14. Identifying the destination or localization of proteins is key to understanding their function and facilitating their purification. A number of existing computational prediction methods are based on sequence analysis. However, these methods are limited in scope, accuracy...
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Spring 2023
For more than 70 years, chemists have used Nuclear Magnetic Resonance (NMR) spectroscopy to characterize the atomic structure and dynamics of molecules. Key to performing the NMR analysis of almost any molecule is a process called “chemical shift assignment”. This involves matching specific peaks...
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Prioritizing Labour Productivity Improvement Strategies by Integrating Hybrid Feature Selection, Fuzzy Multi-Criteria Decision-Making, and Fuzzy Cognitive Maps
DownloadFall 2021
Construction labour productivity (CLP), as a key performance index in the construction sector, is affected by various factors such as crew motivation and working conditions that are highly interconnected and vary on a project-by-project basis. CLP can be enhanced by properly practicing...
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Spring 2013
This work introduces the “online probing” problem: In each round, the learner is able to purchase the values of a subset of features for the current instance. After the learner uses this information to produce a prediction for this instance, it then has the option of paying for seeing the full...
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Fall 2016
The field of biomedicine is reeling from “information overload”. Indeed, biomedical researchers find it almost impossible to stay current with published literature due to the vast amounts of data being generated and published. As a result, they are turning to text mining. Over the past two...
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Fall 2022
The objective of signal decomposition is to extract and separate distinct signal components from a composite signal. Signal decomposition has been studied in many applications, such as image, video, audio, and speech signals. This thesis focuses on the category of signal decomposition on...
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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 2020
Reinforcement learning (RL) has received wide attention in various fields lately. Model-free RL brings data-driven solutions that learn the control strategy directly from interaction with process data without the need for a process model. This is especially beneficial in the case of nonlinear...
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Robust and Accurate Generic Visual Object Tracking Using Deep Neural Networks in Unconstrained Environments
DownloadSpring 2022
The availability of affordable cameras and video-sharing platforms have provided a massive amount of low-cost videos. Automatic tracking of objects of interest in these videos is the essential step for complex visual analyses. As a fundamental computer vision task, Visual Object Tracking aims at...