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.