This paper addresses the problem of segmenting a combination of linear subspaces and quadratic surfaces from sample data points corrupted by (not necessarily small) noise. Our mai...
Necmiye Ozay, Mario Sznaier, Constantino M. Lagoa,...
In [3], we introduced a framework for querying and updating probabilistic information over unordered labeled trees, the probabilistic tree model. The data model is based on trees ...
In this paper we propose and analyze a Stochastic-Collocation method to solve elliptic Partial Differential Equations with random coefficients and forcing terms (input data of the...
We propose a modified discrete HMM that includes a feature weighting discrimination component. We assume that the feature space is partitioned into subspaces and that the relevan...
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...