A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2013; you can also visit the original URL.
The file type is application/pdf
.
Learning Target Predictive Function without Target Labels
2012
2012 IEEE 12th International Conference on Data Mining
In the absence of the labeled samples in a domain referred to as target domain, Domain Adaptation (DA) techniques come in handy. Generally, DA techniques assume there are available source domains that share similar predictive function with the target domain. Two core challenges of DA typically arise, variance that exists between source and target domains, and the inherent source hypothesis bias. In this paper, we first propose a Stability Transfer criterion for selecting relevant source domains
doi:10.1109/icdm.2012.77
dblp:conf/icdm/SeahTOM12
fatcat:zz3r5aj6qrcc5mee3ltqhuhuly