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"

By

Mr. Jialin Pan


Abstract

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