Real Time Learning of Non-stationary Processes with Dynamic Bayesian Networks

DOI10.1007/978-3-319-40596-4_29zbMath1452.68150OpenAlexW2413159633MaRDI QIDQ5115744

Philippe Baumard, Matthieu Hourbracq, Christophe Gonzales, Pierre-Henri Wuillemin

Publication date: 18 August 2020

Published in: Information Processing and Management of Uncertainty in Knowledge-Based Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-40596-4_29

zbMATH Keywords

learningreal timechange pointDBNnon-stationnaryns-DBNtv-DBN

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Probabilistic graphical models (62H22)

Cites Work

• Unnamed Item
• Unnamed Item
• Non-homogeneous dynamic Bayesian networks for continuous data
• Minimum Hellinger distance estimates for parametric models
• Host-based intrusion detection using dynamic and static behavioral models
• Intrusion Detection using Continuous Time Bayesian Networks

This page was built for publication: Real Time Learning of Non-stationary Processes with Dynamic Bayesian Networks