– Probabilistic Inference Networks are becoming increasingly popular for modeling and reasoning in uncertain domains. In the past few years, many efforts have been made in learni...
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
Abstract-- This paper introduces a convex formulation approach for the initialization of parameter estimation problems (PEP). The proposed method exploits the parameter-affine feat...
Julian Bonilla Alarcon, Moritz Diehl, Bart De Moor...
We propose a new fast facial-feature extraction technique for embedded face-recognition applications. A deformable feature model is adopted, of which the parameters are optimized t...
: In this paper the problem of parameter estimation of an input – output system is discussed. It is assumed that the system is described by the relation known with accuracy to so...