Graduate Thesis Or Dissertation

 

Stokes, Gauss, and Bayes walk into a bar... Public Deposited

https://scholar.colorado.edu/concern/graduate_thesis_or_dissertations/gq67jr16q
Abstract
  • This thesis consists of three distinct projects. The first is a study of microbial aggregate fragmentation, in which we develop a dynamical model of aggregate deformation and breakage and use it to obtain a post-fragmentation density function. The second and third projects deal with dimensionality reduction in machine learning problems. In the second project, we derive a one-pass sparsified Gaussian mixture model to perform clustering analysis on high-dimensional streaming data. The model estimates parameters in dense space while storing and performing computations in a compressed space. In the final project, we build an expert system classifier with a Bayesian network for use on high-volume streaming data. Our approach is specialized to reduce the number of observations while obtaining sufficient labeled training data in a regime of extreme class-imbalance and expensive oracle queries.
Creator
Date Issued
  • 2019
Academic Affiliation
Advisor
Committee Member
Degree Grantor
Commencement Year
Subject
Dernière modification
  • 2019-11-15
Resource Type
Déclaration de droits
Language

Des relations

Articles