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Towards a Better Approximation for Sparsest Cut?
2013
2013 IEEE 54th Annual Symposium on Foundations of Computer Science
We give a new (1 + )-approximation for sparsest cut problem on graphs where small sets expand significantly more than the sparsest cut (sets of size n/r expand by a factor √ log n log r bigger, 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
doi:10.1109/focs.2013.37
dblp:conf/focs/AroraGS13
fatcat:ghydgz4r7zaf3ew5rq3awjg7fq