Summary: Spectral Domain-Transfer Learning
Xiao Ling
Wenyuan Dai
Gui-Rong Xue
Qiang Yang
Yong Yu

Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
{shawnling, dwyak, grxue, yyu}@apex.sjtu.edu.cn

Hong Kong University of Science and Technology, Clearway Bay, Kowloon, Hong Kong, China
qyang@cse.ust.hk
ABSTRACT
Traditional spectral classification has been proved to be ef-
fective in dealing with both labeled and unlabeled data when
these data are from the same domain. In many real world
applications, however, we wish to make use of the labeled
data from one domain (called in-domain) to classify the un-
labeled data in a different domain (out-of-domain). This
problem often happens when obtaining labeled data in one

Source: Anderson, Richard - Department of Computer Science and Engineering, University of Washington at Seattle

Collections: Computer Technologies and Information Sciences