K. Shoikhet and D. Geiger. A practical algorithm for finding optimal triangulations. In Proc. National Conference on Artificial Intelligence (AAAI '97), pages 185--190. Morgan Kaufmann, 1997. Home/Search Document Not in Database Summary Related Articles Check |
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Pre-Processing Rules for Triangulation of.. - Bodlaender, Koster.. (2003) (Correct)
....maximum clique size. Recent research results indicate, however, that for small graphs optimal triangulations can be feasibly computed. Building upon a variant of an algorithm by Arnborg, Corneil, and Proskurowski [1] Shoikhet and Geiger performed various experiments on randomly generated graphs [14]. Their results indicate that this algorithm allows for computing optimal triangulations of graphs with up to 100 vertices. The paper is organised as follows. In Section 2, we review some basic definitions. In Section 3, we present our pre processing rules. The computational model in which these ....
....different algorithms can be used. If the algorithm employed is exact, that is, if it yields a triangulation of minimal treewidth, then our method yields an optimal triangulation for the original moralised graph. An example of such an exact algorithm can be found in the work of Shoikhet and Geiger [14], where an implementation is given of a variant of an algorithm of Arnborg, Corneil, and Proskurowski [1] that appears practical for small size networks. For many real life networks, the combination of our reduction rules with an exact algorithm results in an optimal triangulation in reasonable ....
K. Shoikhet and D. Geiger. A practical algorithm for finding optimal triangulations. In Proceedings of the National Conference on Artificial Intelligence (AAAI 97), pp. 185--190. Morgan Kaufmann, 1997. 23
Maximum Likelihood Bounded Tree-Width Markov Networks - Srebro (2002) (9 citations) (Correct)
.... triangulating a graph (since it e#ectively finds a triangulation of the target distribution) But even though triangulation is very di#cult in practice, it can be done in linear time for fixed width k [Bod96] other, more practical algorithms, without such theoretical guarantees, are also known [SG97]) leaving open the possibility for e#cient learning algorithms for small widths. Note that if a constant factor approximation algorithm on the information divergence itself is found, it can also be used for this PAC learning task. It is also interesting to study the weights that carry the ....
Kirill Shoikhet and Dan Geiger. A practical algorithm for finding optimal triangulations. In Proceedings of the Fourteenth National Conference on Artificial Intelligence, pages 185--190, 1997.
Journal of Graph Algorithms and Applications - Http Jgaa Info (2006) (Correct)
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K. Shoikhet and D. Geiger. A practical algorithm for finding optimal triangulations. In Proc. National Conference on Artificial Intelligence (AAAI '97), pages 185--190. Morgan Kaufmann, 1997.
Computations - Hans Bodlaender Department (2006) (Correct)
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K. Shoikhet and D. Geiger. A practical algorithm for finding optimal triangulations. In Proc. National Conference on Artificial Intelligence (AAAI '97), pages 185--190. Morgan Kaufmann, 1997.
Contraction and Treewidth Lower Bounds - Hans Bodlaender Arie (2004) (1 citation) (Correct)
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K. Shoikhet and D. Geiger. A practical algorithm for finding optimal triangulations. In Proc. National Conference on Artificial Intelligence (AAAI '97), pages 185--190. Morgan Kaufmann, 1997.
On Exact Algorithms for Treewidth - Hans Bodlaender Fedor (2006) (Correct)
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K. Shoikhet and D. Geiger. A practical algorithm for finding optimal triangulations. In Proc. National Conference on Artificial Intelligence (AAAI '97), pages 185--190. Morgan Kaufmann, 1997.
Approximation Algorithms for Treewidth - Amir (Correct)
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K. Shoikhet and D. Geiger, A practical algorithm for finding optimal triangulations, in Proc. National Conference on Artificial Intelligence (AAAI '97), Morgan Kaufmann, 1997, pp. 185--190.
A Dynamic Data Structure for Checking Hyperacyclicity - Percy Liang Nathan (2003) (Correct)
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Kirill Shoikhet and Dan Geiger. A practical algorithm for finding optimal triangulations. In Proceedings of the Fourteenth National Conference on Artificial Intelligence, pages 185--190, 1997. 12
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