Abstract. In this paper wepresent an algorithm for parameterfree informationpreserving surface restoration. The algorithm is designed for 2.5D and 3D surfaces. The basic idea is to...
Given discrete event data, we wish to produce a probability density that can model the relative probability of events occurring in a spatial region. Common methods of density esti...
Laura M. Smith, Matthew S. Keegan, Todd Wittman, G...
Abstract – In this paper we seek a Gaussian mixture model (GMM) of the classconditional densities for plug-in Bayes classification. We propose a method for setting the number of ...
In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
We propose novel spatio-temporal models to estimate clickthrough rates in the context of content recommendation. We track article CTR at a fixed location over time through a dynam...