Title :
Towards a Better Approximation for Sparsest Cut?
Author :
Arora, Samarth ; Rong Ge ; Sinop, Ali Kemal
Author_Institution :
Comput. Sci. Dept., Princeton Univ., Princeton, NJ, USA
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.
Keywords :
computational complexity; graph theory; (1 + ε)-approximation; Guruswami-Sinop rounding; level-r Lasserre relaxation; small set expander flow; sparsest cut; Approximation algorithms; Approximation methods; Eigenvalues and eigenfunctions; Games; Graph theory; Particle separators; Vectors; approximation algorithms; expander flows; graph partitioning; small set expansion; sparsest cut;
Conference_Titel :
Foundations of Computer Science (FOCS), 2013 IEEE 54th Annual Symposium on
Conference_Location :
Berkeley, CA
DOI :
10.1109/FOCS.2013.37