We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
Covariance and correlation estimates have important applications in data mining. In the presence of outliers, classical estimates of covariance and correlation matrices are not re...
Fatemah A. Alqallaf, Kjell P. Konis, R. Douglas Ma...
A new parameter estimation method is presented, applicable to many computer vision problems. It operates under the assumption that the data (typically image point locations) are a...
Wojciech Chojnacki, Michael J. Brooks, Anton van d...
Spatial and temporal correlations which affect the signal measured in functional MRI (fMRI) are usually not considered simultaneously (i.e., as non-independent random processes) in...
We introduce an algorithm that simultaneously estimates a classification function as well as its gradient in the supervised learning framework. The motivation for the algorithm is...