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Graph Triangulation

Graph Triangulation. by Dmitry Pidan Based on the paper “A sufficiently fast algorithm for finding close to optimal junction tree” by Ann Becker and Dan Geiger. Definition: junction tree. The natural approach. Example. ==>. ==>. The natural approach. X is called a “ minimum vertex cut ”

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Graph Triangulation

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  1. Graph Triangulation by Dmitry Pidan Based on the paper “A sufficiently fast algorithm for finding close to optimal junction tree” by Ann Becker and Dan Geiger

  2. Definition: junction tree

  3. The natural approach

  4. Example ==> ==>

  5. The natural approach • X is called a “minimum vertex cut” • The main disadvantage – there is no guarantee on the size of the maximal clique in an output triangulated graph

  6. Graph decomposition

  7. Graph decomposition (cont.)

  8. Example a b c d e

  9. Properties of decomposition - Lemma 1

  10. Properties of decomposition - Lemma 2

  11. Triangulation algorithm

  12. Example (one-level recursive call) h a d f c g b e i j k

  13. Trialgulation algorithm - intuition • We use a set W as a “balance factor” between the decomposition sets A, B and C – we are interested that a largest set will be as small as possible. • At every iteration a produced clique is kept small (due to the guarantees of the decomposition)

  14. Triangulation algorithm (cont.)

  15. Proof of correctness • Termination • Validity of the failure statement – follows immediately from Lemma 2 • An output in the case of success is a triangulated graph • Cliquewidth in the case of success is as guaranteed

  16. Proof of correctness (cont.)

  17. Proof of correctness (cont.)

  18. Proof of correctness (cont.)

  19. Finding a decomposition

  20. Finding a decomposition (cont.) • The existence of W-decomposition is checked as follows: • First, a decomposition of graph into disconnected components is found, using approximation algorithm for weighted minimal vertex cut problem • Next, A, B and C components of the decomposition are constructed by unifying the components that contain an appropriate subsets of W

  21. Finding a decomposition (cont.) • Finally, X is constructed from an initial common subset of W and X unified with the vertex cut found. If X stands for the size requirements then the decomposition is a required one. • More formally – in the next 3 slides

  22. The 3-way vertex cut problem • Definition: given a weighted undirected graph and three vertices, find a set of vertices of minimum weight whose removal leaves each of the three vertices disconnected from other two. • Known to be NP-hard • Polynomial approximation algorithms: • A simple 2-approximation algorithm • 4/3-approximation algorithm • Garg N. et al, “Multiway cuts in directed and node-weigthed graphs”

  23. Finding a decomposition: Procedure I

  24. Finding a decomposition: Procedure II

  25. Complexity

  26. Backup slides – proofs and some formalism

  27. Proof of Lemma 1

  28. Proof of Lemma 1 (cont.)

  29. Proof of Lemma 1 (cont.)

  30. Proof of Lemma 2

  31. Proof of Lemma 2 (cont.)

  32. Theorem 1 (formal definition of algorithm correctness)

  33. Finding a decomposition - proof of correctness

  34. Finding a decomposition - proof of correctness (cont.)

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