Search-Based Learning of Latent Tree Models

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "Search-Based Learning of Latent Tree Models"

By

Mr. Tao Chen


Abstract

A latent variable model is a statistical model that relates a set of 
observed variables (aka manifest variables) to a set of unobserved 
variables (aka latent variables). Examples of latent variable models 
include hidden Markov models (HMMs), latent class models, factor models, 
and so on. In this thesis we study a class of latent variable models known 
as latent tree (LT) models. LT models are tree-structured Bayesian 
networks where the leaf nodes represent manifest variables while internal 
nodes represent latent variables. We investigate the automatic induction 
of LT models from data, and the use of LT models in cluster analysis of 
categorical data.

Several search-based algorithms for learning LT models have been 
developed. However there are important issues that remain poorly 
understood. In this thesis we study three such issues, namely operation 
granularity, efficient model evaluation and range of model adjustment. The 
investigation sheds new light on search-based learning of LT models and 
leads to a new algorithm that is conceptually simpler and more efficient 
than the state-of-the-art and yet finds better models.

LT models can be used for latent structure discovery, density estimation 
and cluster analysis. In this thesis we address an issue that is critical 
to the application of LT models to cluster analysis, namely model 
interpretation, and we demonstrate using empirical results that LT 
analysis can discover from data interesting regularities that no other 
methods can.


Date:			Wednesday, 10 December 2008

Time:			10:00a.m.-12:00noon

Venue:			Room 3501
 			Lifts 25-26

Chairman:		Prof. Ross Murch (ECE)

Committee Members:	Prof. Nevin Zhang (Supervisor)
 			Prof. Mordecai Golin
 			Prof. Dit-Yan Yeung
 			Prof. Albert Lo (ISOM)
 			Prof. Finn Verner Jensen (Comp. Sci., Aalborg Univ.)


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