We present a principled Bayesian framework for modeling partial memberships of data points to clusters. Unlike a standard mixture model which assumes that each data point belongs ...
Katherine A. Heller, Sinead Williamson, Zoubin Gha...
Low-frequency variability in geopotential height records of the Northern Hemisphere is a topic of significance in atmospheric science, having profound implications for climate mod...
Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Rod...
In this work, a novel probability distribution is proposed to model sparse directional data. The Directional Laplacian Distribution (DLD) is a hybrid between the linear Laplacian d...
This paper proposed a novel video shot clustering algorithm using spectral method by joint modeling of inter and intra shot. Gauss Mixture Model (GMM) is used for probabilistic sp...
Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design ...