We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
Matching of high-dimensional features using nearest neighbors search is an important part of image matching methods which are based on local invariant features. In this work we hi...
Extracting information from data, often also called data analysis, is an important scienti c task. Statistical approaches, which use methods from probability theory and numerical a...
Bernd Fischer 0002, Johann Schumann, Thomas Pressb...
We consider dense wireless sensor networks deployed to observe arbitrary random fields. The requirement is to reconstruct an estimate of the random field at a certain collector ...
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...