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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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Sequential decision-making in a variable environment: modeling elk movement in Yellowstone National Park as a dynamic game.
Download2007
Potapov, A. B., Noonburg, E. G., Newman, L. A., Lewis, M. A., Crabtree, R. L.
We develop a suite of models with varying complexity to predict elk movement behavior during the winter on the Northern Range of Yellowstone National Park (YNP). The models range from a simple representation of optimal patch choice to a dynamic game, and we show how the underlying theory in each...
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Space plasma instrument concept and analysis using simulation and machine learning techniques
DownloadFall 2022
Much interest has been drawn toward our near-Earth space with the advent of the space-flight era. In order to better understand this highly dynamic environment, the development of measuring instruments for use on near-Earth spacecraft has become particularly important. The current inference...
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Spring 2022
The fifth-generation (5G) and beyond wireless networks aim to increase the current data rates to more than 10 Gbit/s. Thus, the spectrum crunch necessitates increasing spectral efficiency (SE). Key non-orthogonal technologies for this goal are (I) full-duplex wireless, (II) generalized...
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Spring 2012
We study linear estimation based on perturbed data when performance is measured by a matrix norm of the expected residual error, in particular, the case in which there are many unknowns, but the “best” estimator is sparse, or has small L1-norm. We propose a Lasso-like procedure that finds the...
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Fall 2015
Researchers conduct association studies to discover biomarkers in order to gain new biological insight on complex diseases and phenotypes. Although most researchers have intuitions about what defines a biomarker and how to assess the results of an association study, there is neither a formal...
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The challenge of applying machine learning techniques to diagnose schizophrenia using multi-site fMRI data
DownloadSpring 2017
One of the main challenges for the use of machine learning techniques in neuroimaging data is the small n, large p problem. Datasets usually contain only a few hundreds of instances (n), each of which is described using hundreds of thousands of features (p). In this dissertation, we explore the...
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Fall 2012
In a partial-monitoring game a player has to make decisions in a sequential manner. In each round, the player suffers some loss that depends on his decision and an outcome chosen by an opponent, after which he receives "some" information about the outcome. The goal of the player is to keep the...
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Spring 2018
Decision-making problems with two agents can be modeled as two player games, and a Nash equilibrium is the basic solution concept describing good play in adversarial games. Computing this equilibrium solution for imperfect information games, where players have private, hidden information, is...