Talks and Poster Presentations (with Proceedings-Entry):
G. Gottlob, C. Okulmus, R. Pichler:
"Fast and Parallel Decomposition of Constraint Satisfaction Problems";
Talk: IJCAI 2020,
- 2021-01-10; in: "Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, (IJCAI 2020)",
Constraint Satisfaction Problems (CSP) are notoriously hard. Consequently, powerful decomposition methods have been developed to overcome this complexity. However, this poses the challenge of actually computing such a decomposition for a given CSP instance, and previous algorithms have shown their limitations in doing so. In this paper, we present a number of key algorithmic improvements and parallelisation techniques to compute so-called Generalized Hypertree Decompositions (GHDs) faster. We thus advance the ability to compute optimal (i.e., minimal-width) GHDs for a significantly wider range of CSP instances on modern machines. This lays the foundation for more systems and applications in evaluating CSPs and related problems (such as Conjunctive Query answering) based on their structural properties.
Constraints and SAT: Constraint Satisfaction; Multidisciplinary Topics and Applications: Databases
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Project Head Reinhard Pichler:
Created from the Publication Database of the Vienna University of Technology.