Talks and Poster Presentations (with Proceedings-Entry):

V. Ramaswamy, S. Szeider:
"Turbocharging Treewidth-Bounded Bayesian Network Structure Learning";
Talk: 35th AAAI 2021, virtual event; 2021-02-02 - 2021-02-09; in: "Thirty-Fifth AAAI Conference on Artificial Intelligence", AAAI Press, 35 (2021), ISBN: 978-1-57735-866-4; 3895 - 3903.

English abstract:
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

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.