2ima00

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2ima00 [2016/05/26 11:42] bmpjansen [Student lectures] |
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The literature linked to below can be accessed when logged into the TU/e network, either through VPN or by physically being present at TU/e. | The literature linked to below can be accessed when logged into the TU/e network, either through VPN or by physically being present at TU/e. | ||

- | *Kernels: Chris & Leo.* | + | **Kernels: Chris & Leo.** |

+ | | ||

+ | The following paper gives a kernel that is not as small, but is easier to compute, than the one given in the book. In particular, read Section 4 of this paper: | ||

[[http://dx.doi.org/10.1007/s00224-009-9234-2| | [[http://dx.doi.org/10.1007/s00224-009-9234-2| | ||

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A Cubic Kernel for Feedback Vertex Set and Loop Cutset. Theory Comput. Syst. 46(3): 566-597 (2010)]] | A Cubic Kernel for Feedback Vertex Set and Loop Cutset. Theory Comput. Syst. 46(3): 566-597 (2010)]] | ||

- | This uses an approximation algorithm, which was developed independently by 2 sets of authors. Pick the one you find the easiest to read: | + | Instead of requiring an algorithm to find maximum matchings, it just needs an approximation algorithm for (weighted) feedback vertex set. It was developed independently by 2 sets of authors. Pick the one you find the easiest to read: |

Option 1: | Option 1: | ||

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[[https://dx.doi.org/10.1016%2F0004-3702%2895%2900004-6|Becker, Ann; Geiger, Dan (1996), "Optimization of Pearl's method of conditioning and greedy-like approximation algorithms for the vertex feedback set problem.", Artificial Intelligence 83 (1): 167–188]] | [[https://dx.doi.org/10.1016%2F0004-3702%2895%2900004-6|Becker, Ann; Geiger, Dan (1996), "Optimization of Pearl's method of conditioning and greedy-like approximation algorithms for the vertex feedback set problem.", Artificial Intelligence 83 (1): 167–188]] | ||

- | *Treewidth: Henk & Xi.* | + | **Treewidth: Henk & Xi.** |

+ | | ||

+ | There are 2 approaches for solving the problem when you have a tree decomposition. The first one has a running time of 3^k * poly(n), harder to understand, but may be easier to implement: | ||

[[https://arxiv.org/pdf/1103.0534v1.pdf|Cygan et al.: Solving connectivity problems parameterized by treewidth in single exponential time]] | [[https://arxiv.org/pdf/1103.0534v1.pdf|Cygan et al.: Solving connectivity problems parameterized by treewidth in single exponential time]] | ||

+ | |||

+ | The next approach has a worse factor f(k), but a better polynomial term (linear), and is conceptually simpler: | ||

+ | |||

[[http://link.springer.com/chapter/10.1007%2F3-540-36379-3_25|Ton Kloks, C.M. Lee, Jiping Liu. New Algorithms for k-Face Cover, k-Feedback Vertex Set, and k-Disjoint Cycles on Plane and Planar Graphs]] (page 8 and further) | [[http://link.springer.com/chapter/10.1007%2F3-540-36379-3_25|Ton Kloks, C.M. Lee, Jiping Liu. New Algorithms for k-Face Cover, k-Feedback Vertex Set, and k-Disjoint Cycles on Plane and Planar Graphs]] (page 8 and further) | ||

- | *Parameterized by solution size (iterative compression & randomized): Huib & Stefan.* | + | I don't know which of the 2 approaches will be faster on the inputs we have; one has a worse polynomial term, the other has a worse factor f(k). I don't think it is feasible to implement both, given the time. Pick one of the two and go for it. |

+ | | ||

+ | **Parameterized by solution size (iterative compression & randomized): Huib & Stefan.** | ||

[[http://dx.doi.org/10.1016/j.ipl.2014.05.001|Tomasz Kociumaka, Marcin Pilipczuk: | [[http://dx.doi.org/10.1016/j.ipl.2014.05.001|Tomasz Kociumaka, Marcin Pilipczuk: | ||

Faster deterministic Feedback Vertex Set. Inf. Process. Lett. 114(10): 556-560 (2014)]] | Faster deterministic Feedback Vertex Set. Inf. Process. Lett. 114(10): 556-560 (2014)]] |

2ima00.txt · Last modified: 2016/05/26 12:27 by bmpjansen