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Skip to Search Results- 76Machine learning
- 11Online learning
- 5Artificial intelligence
- 5Reinforcement learning
- 3Data mining
- 3Game theory
- 2White, Martha
- 1Afaghi, Mohammad
- 1Ajallooeian, Mohammad Mahdi
- 1Alinezhad, Haniyeh Seyed
- 1Allen, Felicity R
- 1Araya, Ruben
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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...
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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...
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Fall 2016
This thesis focuses on the experimental and theoretical study of various rare-earth transition-metal germanides that contain three or four components. Ternary and quaternary germanides were synthesized through various methods, including direct reaction of the elements, arc-melting, and flux...
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Fall 2021
Pressure swing adsorption (PSA) processes are an industrially mature low energy consumption pathway for gas separations. Due to their performance being linked to the separation media, they provide an additional degree of freedom for process design. They are difficult to accurately model due to...