Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Improved acoustic modeling can significantly decrease the error rate in large-vocabulary speech recognition. Our approach to the problem is twofold. We first propose a scheme that...
Background: Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor...
In this paper, we present preliminary results comparing the nature of the errors introduced by the mixture of principal components (MPC) model with a wavelet transform and the Karh...
This paper considers the problem of monocular human body tracking using learned models. We propose to learn the joint probability distribution of appearance and body pose using a m...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...