Elegir campos a generar del autor Andrés Ramón

Datos personales Todos / Ninguno
Correo Electrónico
Artículos Todos / Ninguno
Learning Styles Impact Students’ Perceptions on Active Learning Methodologies: A Case Study on the Use of Live Coding and Short Programming Exercises
From anecdote to evidence: the relationship between personality and need for cognition of developers
An Empirical Analysis of the Impact of Continuous Assessment on the Final Exam Mark
Probabilistic Models with Deep Neural Networks
InferPy: Probabilistic modeling with deep neural networks made easy
Variational Inference over Nonstationary Data Streams for Exponential Family Models
Comparing two multinomial samples using hierarchical Bayesian models
Analyzing concept drift: A case study in the financial sector
InferPy: Probabilistic modeling with Tensorflow made easy
AMIDST: A Java toolbox for scalable probabilistic machine learning
Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks
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Scaling up Bayesian variational inference using distributed computing clusters
MAP inference in dynamic hybrid Bayesian networks
Probabilistic Graphical Models on Multi-Core CPUs Using Java 8
Learning from incomplete data in Bayesian networks with qualitative influences
Discretization of expression quantitative trait loci in association analysis between genotypes and expression data
Classification with decision trees from a nonparametric predictive inference perspective
Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks
An interactive approach for Bayesian network learning using domain/expert knowledge
New skeleton-based approaches for Bayesian structure learning of Bayesian networks
Bagging schemes on the presence of class noise in classification
A Bayesian stochastic search method for discovering Markov boundaries
Imprecise classification with credal decision trees
A memory efficient semi-Naive Bayes classifier with grouping of cases
A method for integrating expert knowledge when learning bayesian networks from data
An ensemble method using credal decision trees
A filter-wrapper method to select variables for the naive bayes classifier based on credal decision trees
Requirements for total uncertainty measures in Dempster-Shafer theory of evidence
Varying parameter in classification based on imprecise probabilities
Libros, capítulos, tesis Todos / Ninguno
Un test de dos muestras multinomiales basado en modelos bayesianos jerárquicos
Virtual subconcept drift detection in discrete data using probabilistic graphical models
Classification
Models of supervised classification. Applications to genomics and information retrieval
Conferencias Todos / Ninguno
Learning under model misspecification: Applications to variational and ensemble methods
Second order PAC-Bayesian bounds for the weighted majority vote
Variational Robust Subspace Clustering with Mean Update Algorithm
Bayesian models of data streams with Hierarchical Power Priors
Financial Data Analysis with PGMs Using AMIDST
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach
Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs
d-VMP: Distributed Variational Message Passing
Dynamic Bayesian modeling for risk prediction in credit operations
Modeling concept drift: A probabilistic graphical model based approach
Parallel importance sampling in conditional linear Gaussian networks
Stochastic discriminative em
Locally averaged Bayesian Dirichlet metrics for learning the structure and the parameters of Bayesian networks
A new framework for learning generalized credal networks
Haplotype-based classifiers to predict individual susceptibility to complex diseases: An example for multiple sclerosis
An interactive approach for cleaning noisy observations in Bayesian networks with the help of an expert
Riskoweb: Web-based genetic profiling to complex disease using genome-wide SNP markers
Locally averaged bayesian dirichlet metrics
Learning with Bayesian networks and probability trees to approximate a joint distribution
Comparing binary and standard probability trees in credal networks inference
Link-based text classification using Bayesian networks
An importance sampling approach to integrate expert knowledge when learning Bayesian networks from data
Bagging decision trees on data sets with classification noise
A Bayesian random split to build ensembles of classification trees
An experimental study about simple decision trees for bagging ensemble on datasets with classification noise
A Bayesian approach to estimate probabilities in classification trees
Evaluating query-independent object features for relevancy prediction
Effects of highly agreed documents in relevancy prediction
A semi-naive bayes classifier with grouping of cases
Split criterions for variable selection using decision trees
Combining decision trees based on imprecise probabilities and uncertainty measures
Selective gaussian naïve bayes model for Diffuse Large-B-Cell Lymphoma classification: Some improvements in preprocessing and variable elimination
Methods to determine the branching attribute in Bayesian multinets classifiers
Informes y otros Todos / Ninguno
Rejoinder on "imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks"
Métricas del autor Todos / Ninguno
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