Elegir campos a generar del autor Helge

Datos personales Todos / Ninguno
Correo Electrónico
Artículos Todos / Ninguno
Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation
Applying Bayesian optimization to predict parameters in a time-domain model for cross-flow vortex-induced vibrations
Deep Contextual Grid Triplet Network for Context-Aware Recommendation
Machine Learning in Financial Market Surveillance: A Survey
Probabilistic Models with Deep Neural Networks
Variational Inference over Nonstationary Data Streams for Exponential Family Models
Analyzing concept drift: A case study in the financial sector
Application of data-driven models in the analysis of marine power systems
Learning similarity measures from data
AMIDST: A Java toolbox for scalable probabilistic machine learning
A review of inference algorithms for hybrid Bayesian networks
Effective hate-speech detection in Twitter data using recurrent neural networks
A deep network model for paraphrase detection in short text messages
Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks
A parallel algorithm for Bayesian network structure learning from large data sets
Scaling up Bayesian variational inference using distributed computing clusters
MAP inference in dynamic hybrid Bayesian networks
Short-Term Load Forecasting With Seasonal Decomposition Using Evolution for Parameter Tuning
Scalable learning of probabilistic latent models for collaborative filtering
Learning Mixtures of Truncated Basis Functions from Data
A classification-based approach to monitoring the safety of dynamic systems
A latent model for collaborative filtering
Frontiers in Artificial Intelligence and Applications: Preface
Parameter Estimation and Model Selection for Mixtures of Truncated Exponentials
Maximum Likelihood Learning of Conditional MTE Distributions
Latent Classification Models for Binary Data
Inference in hybrid Bayesian networks
Bayesian networks in reliability
Modelling of dependence between critical failure and preventive maintenance: The repair alert model
Competing risks for repairable systems: A data study
Classification using Hierarchical Naïve Bayes models
Latent classification models
Failure modeling and maintenance optimization for a railway line
Fusion of domain knowledge with data for structural learning in object oriented domains
Decision theoretic troubleshooting of coherent systems
The SACSO methodology for troubleshooting complex systems
Parameter learning in object-oriented Bayesian networks
Uncertainty bounds for a monotone multistate system
Analysis of OREDA data for maintenance optimisation
Libros, capítulos, tesis Todos / Ninguno
Learning hybrid bayesian networks using mixtures of truncated basis functions. Aprendizaje de redes bayesianas híbridas con mixturas de funciones base truncadas
Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions
Bayesian networks in reliability: The good, the bad, and the ugly
Applications of Bayesian networks in reliability analysis
Conferencias Todos / Ninguno
Bayesian Exploration in Deep Reinforcement Learning
Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders
On Reporting Robust and Trustworthy Conclusions from Model Comparison Studies Involving Neural Networks and Randomness
Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches
Comparative study of event prediction in power grids using supervised machine learning methods
Prediction intervals: Split normal mixture from quality-driven deep ensembles
Forecasting intra-hour imbalances in electric power systems
Understanding and improving recurrent networks for human activity recognition by continuous attention
Inter-session modeling for session-based recommendation
Bayesian models of data streams with Hierarchical Power Priors
Content-Based Social Recommendation with Poisson Matrix Factorization
Data driven case base construction for prediction of success of marine operations
Financial Data Analysis with PGMs Using AMIDST
d-VMP: Distributed Variational Message Passing
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach
Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs
Probability-based approach for predicting e-commerce consumer behaviour using sparse session data
MPE inference in conditional linear gaussian networks
Dynamic Bayesian modeling for risk prediction in credit operations
Modeling concept drift: A probabilistic graphical model based approach
Learning conditional distributions using mixtures of truncated basis functions
Parallel importance sampling in conditional linear Gaussian networks
Parallelisation of the PC Algorithm
Learning to rank for personalised fashion recommender systems via implicit feedback
A new method for vertical parallelisation of TAN learning based on balanced incomplete block designs
Effects of data cleansing on load prediction algorithms
Effects of scale on load prediction algorithms
Beating the bookie: A look at statistical models for prediction of football matches
Fast approximate inference in hybrid Bayesian networks using dynamic discretisation
Mixtures of truncated basis functions
A hybrid CBR and BN architecture refined through data analysis
Extended abstract: Combining CBR and BN using metareasoning
Extended abstract: A design for a tourist CF system
Parameter learning in MTE networks using incomplete data
Towards a more expressive model for dynamic classification
Architectures integrating case-based reasoning and Bayesian networks for clinical decision support
Local-global-learning of naive Bayesian classifier
Parameter estimation in mixtures of truncated exponentials
Métricas del autor Todos / Ninguno
Indice H