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Skip to Search Results- 101Machine learning
- 21Online learning
- 9Artificial intelligence
- 7Reinforcement learning
- 3Data mining
- 3Game theory
- 4Hindle, Abram
- 4Mark A. Lewis
- 4Russell Greiner
- 3Noonari, Juned (Supervisor)
- 3Pouria Ramazi
- 2Bowling, Michael
- 84Graduate and Postdoctoral Studies (GPS), Faculty of
- 84Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 7Master of Science in Internetworking (MINT)
- 7Master of Science in Internetworking (MINT)/Capstone Projects & Reports (Master of Science in Internetworking (MINT))
- 7Communications and Technology Graduate Program
- 7Communications and Technology Graduate Program/Capping Projects (Communications and Technology)
- 84Thesis
- 16Report
- 6Article (Published)
- 5Article (Draft / Submitted)
- 3Conference/Workshop Poster
- 3Research Material
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Motivation and the information behaviours of online learning students: the case of a professionally-oriented, graduate program
DownloadFall 2010
Online learning is a wonderful opportunity for students who cannot attend classes at conventional times and places to further their education. However, to some extent, accessing and sharing information is often quite different and potentially more difficult for this particular group (e.g., they...
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2012
Bowling, Michael, Zinkevich, Martin
Online learning aims to perform nearly as well as the best hypothesis in hindsight. For some hypothesis classes, though, even finding the best hypothesis offline is challenging. In such offline cases, local search techniques are often employed and only local optimality guaranteed. For online...
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Spring 2016
Ideal agent behaviour in multiagent environments depends on the behaviour of other agents. Consequently, acting to maximize utility is challenging since an agent must gather and exploit knowledge about how the other (potentially adaptive) agents behave. In this thesis, we investigate how an...
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Fall 2016
In an online learning problem a player makes decisions in a sequential manner. In each round, the player receives some reward that depends on his action and an outcome generated by the environment while some feedback information about the outcome is revealed. The goal of the player can be...
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Spring 2022
In this dissertation, we study online off-policy temporal-difference learning algorithms, a class of reinforcement learning algorithms that can learn predictions in an efficient and scalable manner. The contributions of this dissertation are one of the two kinds: (1) empirically studying existing...
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Optimal Mechanisms for Machine Learning: A Game-Theoretic Approach to Designing Machine Learning Competitions
DownloadSpring 2013
In this thesis we consider problems where a self-interested entity, called the principal, has private access to some data that she wishes to use to solve a prediction problem by outsourcing the development of the predictor to some other parties. Assuming the principal, who needs the machine...
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Fall 2014
In the face of an overwhelmingly information intensive Internet, searching has become the most important way to locate information efficiently. Current searching techniques are able to retrieve relevant data, however, personalization techniques are still needed to better identify different user...
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Fall 2015
Polarity classification in text is the problem of automatically detecting the general opinion of textual data. Analyzing the general opinion toward a topic of interest is important for different audiences, such as companies, politicians or even regular users. On the other hand, the availability of...
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Fall 2009
Understanding biochemical reactions inside cells of individual organisms is a key factor for improving our biological knowledge. Signaling pathways provide a road map for a wide range of these chemical reactions that convert one signal or stimulus into another. In general, each signaling pathway...
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2021-10-01
Pouria Ramazi, Mélodie Kunegel-Lion, Russell Greiner, Mark A. Lewis
Planning forest management relies on predicting insect outbreaks such as mountain pine beetle, particularly in the intermediate‐term future, e.g., 5‐year. Machine‐learning algorithms are potential solutions to this challenging problem due to their many successes across a variety of prediction...