Speaker: Professor Pedro Larrañaga
Title: Discrete Bayesian network classifiers
Time: 14:30-15:30, April 28th, 2023 (Friday)
Website: Teams Link
Abstract:
During the talk, we will introduce several types of Bayesian network classifiers for discrete predictor variables: Naive Bayes, selective naive Bayes, seminaive Bayes, one-dependence Bayesian classifiers, k-dependence Bayesian classifiers, Bayesian network-augmented naive Bayes, Markov blanket-based Bayesian classifier, unrestricted Bayesian classifiers, and Bayesian multinets. The decision boundaries associated to each of these models will also be presented. The interpretation inherent in these models will be shown with an example from neuroanatomy.
Personal Introduction:
Pedro Larrañaga is Full Professor in Computer Science and Artificial Intelligence at the Universidad Politécnica de Madrid. He received the MSc degree in Mathematics (Statistics) from the University of Valladolid and the PhD degree in Computer Science from the University of the Basque Country (Excellence Award). His research interests are primarily in the areas of probabilistic graphical models, metaheuristics for optimization, machine learning classification models, and real applications, like biomedicine, bioinformatics, neuroscience, industry 4.0 and sports. He has published more than 200 papers in high impact factor journals and has supervised more than 30 PhD theses. He is fellow of the European Association for Artificial Intelligence since 2012 and fellow of the Academia European and of the Asia-Pacific Artificial Intelligence Association since 2018 and 2021 respectively. He has been awarded the 2013 Spanish National Prize in Computer Science, the prize of the Spanish Association for Artificial Intelligence in 2018 and the Amity Research Award in Machine Learning in New Delhi, in 2020. Recently he has been elected as member of Jakiunde, the Academy of Sciences, Arts and Letters of the Basque Country. He leads the ELLIS Unit Madrid.
[Editor:Xiaohan Liu]