In this paper, we propose a new semi-supervised training method for Gaussian Mixture Models. We add a conditional entropy minimizer to the maximum mutual information criteria, whi...
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
An important aspect of collaborative information seeking (CIS) is making sense of the information found, i.e., collaborative sensemaking. We conducted an ethnographic study of the...
We extend a recent Sparse Representation-based Classification (SRC) algorithm for face recognition to work on 2D images directly, aiming to reduce the computational complexity whil...