A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Activity recognition with the aid of unlabeled samples
2009
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication - ICUIMC '09
Activity recognition is an important topic in ubiquitous computing. In activity recognition, supervised learning techniques have been widely applied to learn the activity models. However, most of them can only utilize labeled samples for learning even though a large amount of unlabeled samples exist. In our previous work, we have proposed a semi-supervised learning method which can utilize both labeled and unlabeled samples for learning. As an alternative, a new learning method is proposed in
doi:10.1145/1516241.1516359
dblp:conf/icuimc/GuanLL09
fatcat:dt3u6dg3gjcbdl6f3jdtc4h3gu