We present a new class of models for high-dimensional nonparametric regression and classification called sparse additive models (SpAM). Our methods combine ideas from sparse line...
Pradeep D. Ravikumar, Han Liu, John D. Lafferty, L...
The bootstrap has become a popular method for exploring model (structure) uncertainty. Our experiments with artificial and realworld data demonstrate that the graphs learned from...
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linea...
Nicolas Dobigeon, Jean-Yves Tourneret, Chein-I Cha...
The research field of transportation demand forecasting has started to focus on disaggregate travel behavior and micro-simulation models. To create data infrastructure, disaggrega...
Ali Frihida, Danielle J. Marceau, Marius Thé...
A block based video coder that supports multiple motion models is proposed. Apart from the typical translational motion model, we employ parametric models to more accurately repre...
Haricharan Lakshman, Heiko Schwarz, Thomas Wiegand