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Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

V. Ramaswamy, S. Szeider:
"Turbocharging Treewidth-Bounded Bayesian Network Structure Learning";
Vortrag: 35th AAAI 2021, virtual event; 02.02.2021 - 09.02.2021; in: "Thirty-Fifth AAAI Conference on Artificial Intelligence", AAAI Press, 35 (2021), ISBN: 978-1-57735-866-4; S. 3895 - 3903.



Kurzfassung englisch:
We present a new approach for learning the structure of a
treewidth-bounded Bayesian Network (BN). The key to our
approach is applying an exact method (based on MaxSAT)
locally, to improve the score of a heuristically computed BN.
This approach allows us to scale the power of exact methods-
so far only applicable to BNs with several dozens of random
variables-to large BNs with several thousands of random
variables. Our experiments show that our method improves the
score of BNs provided by state-of-the-art heuristic methods,
often significantly


Elektronische Version der Publikation:
https://publik.tuwien.ac.at/files/publik_300060.pdf


Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.