Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data in...
Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan ...
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
We propose a method for segmentation of frontal human portraits from arbitrary unknown backgrounds. Semantic information is used to project the face into a normalized reference fr...
David C. Schneider, Benjamin Prestele, Peter Eiser...
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
The overwhelming success of the Web as a mechanism for facilitating information retrieval and for conducting business transactions has led to an increase in the deployment of comp...
Bowei Xi, Zhen Liu, Mukund Raghavachari, Cathy H. ...