Although they have potential, to date location-based information systems have not radically improved the way we interact with our surroundings. To study related issues, we develop...
Pamela J. Ludford, Dan Frankowski, Ken Reily, Kurt...
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
In numerous applications of image processing, e.g. astronomical and medical imaging, data-noise is well-modeled by a Poisson distribution. This motivates the use of the negative-lo...
We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-sup...
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...