9 citations · 41 across the 15 of their papers we have counts for
5 papers · 1 filter
Towards Gaussian Bayesian Network Fusion
Irene Córdoba, Concha Bielza, Pedro Larrañaga
Data sets are growing in complexity thanks to the increasing facilities we have nowadays to both generate and store data. This poses many challenges to machine learning that are le…
Markov Property in Generative Classifiers
Gherardo Varando, Concha Bielza, Pedro Larrañaga +1
We show that, for generative classifiers, conditional independence corresponds to linear constraints for the induced discrimination functions. Discrimination functions of undirecte…
A fast Metropolis-Hastings method for generating random correlation matrices
Irene Córdoba, Gherardo Varando, Concha Bielza +1
We propose a novel Metropolis-Hastings algorithm to sample uniformly from the space of correlation matrices. Existing methods in the literature are based on elaborated representati…
A partial orthogonalization method for simulating covariance and concentration graph matrices
Irene Córdoba, Gherardo Varando, Concha Bielza +1
Structure learning methods for covariance and concentration graphs are often validated on synthetic models, usually obtained by randomly generating: (i) an undirected graph, and (i…
Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks
Irene Córdoba, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato +2
The PC algorithm is a popular method for learning the structure of Gaussian Bayesian networks. It carries out statistical tests to determine absent edges in the network. It is henc…