This paper studies the outlier detection problem from the point of view of penalized regressions. Our regression model adds one mean shift parameter for each of the n data points....
We study on-line generalized linear regression with multidimensional outputs, i.e., neural networks with multiple output nodes but no hidden nodes. We allow at the final layer tra...
Background: In vertebrates, a large part of gene transcriptional regulation is operated by cisregulatory modules. These modules are believed to be regulating much of the tissue-sp...
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Given the facial points extracted from an image of a face in an arbitrary pose, the goal of facial-point-based headpose normalization is to obtain the corresponding facial points ...