Variational maximization-maximization of Bayesian mixture models and application to unsupervised image classification

This thesis mainly propose variational inference for Bayesian mixture models and their applications to solve machine learning problems. The mixture models addressed are the Gaussian mixture model (GMM), Dirichlet process mixture (DPM), the sparse coding based Gaussian mixture model (sGMM) and the Fi...

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Bibliographic Details
Main Author: Lim, Kart-Leong
Other Authors: Wang Han
Format: Theses and Dissertations
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/73199
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Institution: Nanyang Technological University
Language: English

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