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How Much of a Hypertree can be Captured by Windmills?
| dc.contributor.author | Liang, Percy | |
| dc.contributor.author | Srebro, Nati | |
| dc.contributor.other | Algorithms | |
| dc.date.accessioned | 2005-12-22T02:20:23Z | |
| dc.date.available | 2005-12-22T02:20:23Z | |
| dc.date.issued | 2005-01-03 | |
| dc.identifier.other | MIT-CSAIL-TR-2005-002 | |
| dc.identifier.other | MIT-LCS-TR-978 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/30515 | |
| dc.description.abstract | Current approximation algorithms for maximum weight {\em hypertrees} find heavy {\em windmill farms}, and are based on the fact that a constant ratio (for constant width $k$) of the weight of a $k$-hypertree can be captured by a $k$-windmill farm. However, the exact worst case ratio is not known and is only bounded to be between $1/(k+1)!$ and $1/(k+1)$. We investigate this worst case ratio by searching for weighted hypertrees that minimize the ratio of their weight that can be captured with a windmill farm. To do so, we use a novel approach in which a linear program is used to find ``bad'' inputs to a dynamic program. | |
| dc.format.extent | 12 p. | |
| dc.format.extent | 13845223 bytes | |
| dc.format.extent | 531507 bytes | |
| dc.format.mimetype | application/postscript | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en_US | |
| dc.relation.ispartofseries | Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory | |
| dc.title | How Much of a Hypertree can be Captured by Windmills? |
