— In a data-mining approach, a model for estimation of Aerosol Optical Depth (AOD) from satellite observations is learned using collocated satellite and groundbased observations....
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
When reliable prior bounds on the acceptable errors between the data and corresponding model outputs are available, bounded-error estimation techniques make it possible to characte...
Luc Jaulin, Michel Kieffer, Eric Walter, Dominique...
Hashing is fundamental to many algorithms and data structures widely used in practice. For theoretical analysis of hashing, there have been two main approaches. First, one can ass...
The problem of computing a maximum a posteriori (MAP) configuration is a central computational challenge associated with Markov random fields. There has been some focus on “tr...
Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwr...