Abstract. This paper explores using information about program branch probabilities to optimise reconfigurable designs. The basic premise is to promote utilization by dedicating mo...
In an uncertain database, each data item is modeled as a range associated with a probability density function. Previous works for this kind of data have focussed on simple queries...
We present an algorithm to generate samples from probability distributions on the space of curves. Traditional curve evolution methods use gradient descent to find a local minimum...
Ayres C. Fan, John W. Fisher III, Jonathan Kane, A...
This work justifies several quantum gate level fault models and discusses the causal error mechanisms thwarting correct function. A quantum adaptation of the classical test set gen...
Jacob D. Biamonte, Jeff S. Allen, Marek A. Perkows...
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
Raquel Urtasun, David J. Fleet, Aaron Hertzmann, P...