Feature-based Transfer Learning with Real-world Applications

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

PhD Thesis Defence

Title: "Feature-based Transfer Learning with Real-world Applications"


Mr. Jialin Pan


Transfer learning is a new machine learning and data mining framework that 
allows the training and test data to come from different distributions 
and/or feature spaces. We can find many novel applications of machine 
learning and data mining where transfer learning is helpful, especially 
when we have limited labeled data in our domain of interest. In this 
thesis, we first survey different settings and approaches of transfer 
learning and give a big picture of the field. We focus on latent space 
learning for transfer learning, which aims at discovering a “good” common 
feature space across domain, such that knowledge transfer become possible. 
In our study, we propose a novel dimensionality reduction framework for 
transfer learning, which tries to reduce the distance between different 
domains while preserve data properties as much as possible. This framework 
is general for many transfer learning problems when domain knowledge is 
unavailable. Based on this framework, we propose three effective solutions 
to learn the latent space for transfer learning. We apply these methods to 
two diverse applications: cross-domain WiFi localization and cross-domain 
text classification, and achieve promising results. Furthermore, for a 
specific application area, such as sentiment classification, where domain 
knowledge is available for encoding to transfer learning methods, we 
propose a spectral feature alignment algorithm for cross-domain learning. 
In this algorithm, we try to align domain-specific features from different 
domains by using some domain independent features as a bridge. 
Experimental results show that this method outperforms a state-of-the-art 
algorithm in two real-world datasets on cross-domain sentiment 

Date:			Friday, 17 September 2010

Time:			2:00pm – 4:00pm

Venue:			Room 3301A
 			Lifts 17/18

Chairman:		Prof. Chak-Keung Chan (CBME)

Committee Members:	Prof. Qiang Yang (Supervisor)
 			Prof. James Kwok
 			Prof. Dit-Yan Yeung
                      	Prof. Fugee Tsung (IELM)
                         Prof. Jieping Ye (Comp. Sci. & Engg.,
 					  Arizona State Univ.)

**** ALL are Welcome ****