Manuel Gómez-Olmedo

发表

A Bayesian approach to abrupt concept drift

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2019, Knowl. Based Syst..

Application of a hill-climbing algorithm to exact and approximate inference in credal networks

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2005, ISIPTA.

Heuristics for Determining the Elimination Ordering in the Influence Diagram Evaluation with Binary Trees

Anders L. Madsen, Rafael Cabañas, Andrés Cano, 2013, SCAI.

Using Binary Trees for the Evaluation of Influence Diagrams

Rafael Cabañas, Andrés Cano, Manuel Gómez-Olmedo, 2016, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Binary Probability Trees for Bayesian Networks Inference

Serafín Moral, Andrés Cano, Manuel Gómez-Olmedo, 2009, ECSQARU.

Virtual Subconcept Drift Detection in Discrete Data Using Probabilistic Graphical Models

Andrés R. Masegosa, Rafael Cabañas, Andrés Cano, 2018, IPMU.

Measures of divergence on credal sets

Joaquín Abellán, Manuel Gómez-Olmedo, 2006, Fuzzy Sets Syst..

On SPI-Lazy Evaluation of Influence Diagrams

Anders L. Madsen, Rafael Cabañas, Andrés Cano, 2014, Probabilistic Graphical Models.

Approximate Lazy Evaluation of Influence Diagrams

Anders L. Madsen, Rafael Cabañas, Andrés Cano, 2013, CAEPIA.

Development of the XML Digital Library from the Parliament of Andalucía for Intelligent Structured Retrieval

Juan M. Fernández-Luna, Juan F. Huete, Carlos J. Martín-Dancausa, 2008, ISMIS.

Learning Recursive Probability Trees from Data

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2013, CAEPIA.

Locally Averaged Bayesian Dirichlet Metrics

Andrés R. Masegosa, Serafín Moral, Andrés Cano, 2011, ECSQARU.

Recursive Probability Trees for Bayesian Networks

Serafín Moral, Andrés Cano, Cora B. Pérez-Ariza, 2009, CAEPIA.

Extended Probability Trees for Probabilistic Graphical Models

Andrés Cano, Cora B. Pérez-Ariza, Serafín Moral, 2014, Probabilistic Graphical Models.

Inference in Bayesian Networks with Recursive Probability Trees: Data Structure Definition and Operations

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2013, Int. J. Intell. Syst..

Evaluating Asymmetric Decision Problems with Binary Constraint Trees

Rafael Cabañas, Andrés Cano, Manuel Gómez-Olmedo, 2013, ECSQARU.

Improvements to Variable Elimination and Symbolic Probabilistic Inference for evaluating Influence Diagrams

Anders L. Madsen, Rafael Cabañas, Andrés Cano, 2016, Int. J. Approx. Reason..

Some Variations on the PC Algorithm

Joaquín Abellán, Serafín Moral, Manuel Gómez-Olmedo, 2006, Probabilistic Graphical Models.

Learning with Bayesian networks and probability trees to approximate a joint distribution

Andrés Cano, Manuel Gómez-Olmedo, A. Masegosa, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

Varying Parameter in Classification Based on Imprecise Probabilities

Andrés R. Masegosa, Serafín Moral, Joaquín Abellán, 2006, SMPS.

Applying Numerical Trees to Evaluate Asymmetric Decision Problems

Andrés Cano, Manuel Gómez-Olmedo, 2003, ECSQARU.

Estimating Conditional Probabilities by Mixtures of Low Order Conditional Distributions

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2017, SUM.

MPE Computation in Bayesian Networks Using Mini-Bucket and Probability Trees Approximation

Serafín Moral-García, Andrés Cano, Serafín Moral, 2020, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Evaluating interval-valued influence diagrams

Rafael Cabañas, Alessandro Antonucci, Andrés Cano, 2017, Int. J. Approx. Reason..

A Decision-Based Approach for Recommending in Hierarchical Domains

Luis M. de Campos, Juan M. Fernández-Luna, Juan F. Huete, 2005, ECSQARU.

Learning Sets of Bayesian Networks

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2020, IPMU.

Locally averaged Bayesian Dirichlet metrics for learning the structure and the parameters of Bayesian networks

Andrés R. Masegosa, Serafín Moral, Andrés Cano, 2013, Int. J. Approx. Reason..

Fast Factorisation of Probabilistic Potentials and its Application to Approximate Inference in Bayesian Networks

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2012, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Fast Factorization of Probability Trees and Its Application to Recursive Trees Learning

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2010, SMPS.

Learning recursive probability trees from probabilistic potentials

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2012, Int. J. Approx. Reason..

Variable Elimination for Interval-Valued Influence Diagrams

Rafael Cabañas, Alessandro Antonucci, Andrés Cano, 2015, ECSQARU.

Learning marginal AMP chain graphs under faithfulness revisited

José M. Peña, Manuel Gómez-Olmedo, J. Peña, 2016, Int. J. Approx. Reason..

Hill-climbing and branch-and-bound algorithms for exact and approximate inference in credal networks

Serafín Moral, Joaquín Abellán, Andrés Cano, 2007, Int. J. Approx. Reason..

On SPI for Evaluating Influence Diagrams

Anders L. Madsen, Rafael Cabañas, Andrés Cano, 2014, IPMU.

Approximate Counting of Graphical Models via MCMC Revisited

José M. Peña, Manuel Gómez-Olmedo, Dag Sonntag, 2015, Int. J. Intell. Syst..

Special Issue on PGM-2012

Thomas D. Nielsen, Manuel Gómez-Olmedo, Andrés Cano, 2014, Int. J. Approx. Reason..

A forward-backward Monte Carlo method for solving influence diagrams

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2006, Int. J. Approx. Reason..

Approximate inference in Bayesian networks using binary probability trees

Serafín Moral, Andrés Cano, Manuel Gómez-Olmedo, 2011, Int. J. Approx. Reason..

An Extended Approach to Learning Recursive Probability Trees from Data

Andrés Cano, Cora B. Pérez-Ariza, Manuel Gómez-Olmedo, 2015, Int. J. Intell. Syst..

Credal Nets with Probabilities Estimated with an Extreme Imprecise Dirichlet Model

Andrés Cano, Manuel Gómez-Olmedo, A. Cano, 2007 .