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Skip to Search Results- 101Machine learning
- 21Game theory
- 10Artificial intelligence
- 7Poker
- 5Reinforcement learning
- 4Regret minimization
- 4Hindle, Abram
- 4Mark A. Lewis
- 4Russell Greiner
- 3Johanson, Michael
- 3Noonari, Juned (Supervisor)
- 3Pouria Ramazi
- 88Graduate and Postdoctoral Studies (GPS), Faculty of
- 88Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 8Computing Science, Department of
- 7Master of Science in Internetworking (MINT)
- 7Master of Science in Internetworking (MINT)/Capstone Projects & Reports (Master of Science in Internetworking (MINT))
- 6Biological Sciences, Department of
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Public Health Applications Using Big Data and Machine Learning Methods: Name- and Location-based Aboriginal Ethnicity Classification and Sentiment Analysis of Breast Cancer Screening in the United States Using Twitter
DownloadFall 2017
Applications using big data and machine learning techniques are transforming how people live in the 21st century, however they are generally underutilized in public health compared to other domains. We proposed and conducted two independent studies to investigate how big data and machine learning...
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Fall 2018
Gaussian processes are flexible probabilistic models for regression and classification. However, their success hinges on a well-specified kernel that can capture the structure of data. For complex data, the task of hand crafting a kernel becomes daunting. In this thesis, we propose new methods...
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Regret Minimization in Games and the Development of Champion Multiplayer Computer Poker-Playing Agents
DownloadSpring 2014
Recently, poker has emerged as a popular domain for investigating decision problems under conditions of uncertainty. Unlike traditional games such as checkers and chess, poker exhibits imperfect information, varying utilities, and stochastic events. Because of these complications, decisions at...
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2007
Bowling, Michael, Johanson, Michael, Zinkevich, Martin, Piccione, Carmelo
Technical report TR07-14. Extensive games are a powerful model of multiagent decision-making scenarios with incomplete information. Finding a Nash equilibrium for very large instances of these games has received a great deal of recent attention. In this paper, we describe a new technique for...
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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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Research on IoT Threats & Implementation of AI/ML to Address Emerging Cybersecurity Issues in IoT with Cloud Computing
Download2022-03-31
Internet of Things (IoT) has become one of the progressive innovations and inviting space of interest for the research world and financially captivating for the business world. Integrating different devices and associating devices with humans requires artificial intelligence/ machine learning...
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Research, Implementation and Security Analysis of Connected and Autonomous Vehicles (CAVs) using Machine Learning Algorithms
Download2022-03-17
Efforts linked to connected and autonomous vehicles (CAVs) have exploded in the last several years, and they are already beginning to impact people's daily lives. A growing number of businesses and academic institutions have made public announcements about their CAV efforts, and a few have even...
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Spring 2024
Urban stormwater quality is a critical concern in urban planning and stormwater management due to its significant influence on receiving water bodies and ecosystems. The dynamics of stormwater quality is influenced by complex factors, with rainfall characteristics and land-use/land cover (LULC)...
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Fall 2017
The importance of anchor ice transport of sediment on a river is significantly understudied. This study addresses the lack of data related to anchor ice release and rafting. A large sample set of anchor ice was collected in the field over the 2015-2016 and 2016-2017 winter seasons to compute a...