Towards a better approximation for SPARSEST CUT?
Author(s): Arora, Sanjeev; Ge, R; Sinop, AK
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Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Arora, Sanjeev | - |
dc.contributor.author | Ge, R | - |
dc.contributor.author | Sinop, AK | - |
dc.date.accessioned | 2019-08-29T17:04:48Z | - |
dc.date.available | 2019-08-29T17:04:48Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.citation | Arora, S, Ge, R, Sinop, AK. (2013). Towards a better approximation for SPARSEST CUT?. 270 - 279. doi:10.1109/FOCS.2013.37 | en_US |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/pr1ct7h | - |
dc.description.abstract | We give a new (1 + ε)-approximation for SPARSEST CUT problem on graphs where small sets expand significantly more than the sparsest cut (expansion of sets of size n/r exceeds that of the sparsest cut by a factor √ log n log r, for some small r; this condition holds for many natural graph families). We give two different algorithms. One involves Guruswami-Sinop rounding on the level-r Lasserre relaxation. The other is combinatorial and involves a new notion called Small Set Expander Flows (inspired by the expander flows of [1]) which we show exists in the input graph. Both algorithms run in time 2O(r)poly(n). We also show similar approximation algorithms in graphs with genus g with an analogous local expansion condition. This is the first algorithm we know of that achieves (1 + ε)-approximation on such general family of graphs. | en_US |
dc.format.extent | 270 - 279 | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartof | Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS | en_US |
dc.rights | Author's manuscript | en_US |
dc.title | Towards a better approximation for SPARSEST CUT? | en_US |
dc.type | Conference Article | en_US |
dc.identifier.doi | doi:10.1109/FOCS.2013.37 | - |
pu.type.symplectic | http://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceeding | en_US |
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Towards a better approximation for sparsest cut.pdf | 470.15 kB | Adobe PDF | View/Download |
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