Sparsest Cut on Quotients of the Hypercube
نویسندگان
چکیده
We present a simple construction and analysis of an Ω(log log N) integrality gap for the wellknown Sparsest Cut semi-definite program (SDP). This holds for the uniform demands version (i.e. edge expansion). The same quantitative gap was proved earlier by Devanur, Khot, Saket, and Vishnoi [STOC 2006], following an integrality gap for non-uniform demands due to Khot and Vishnoi [FOCS 2005]. These previous constructions involve a complicated SDP solution and analysis, while our gap instance, vector solution, and analysis are somewhat simpler and more intuitive. Furthermore, our approach is rather general, and provides a variety of different gap examples derived from quotients of the hypercube. It also illustrates why the lower bound is stuck at Ω(log log N), and why new ideas are needed in order to derive stronger examples.
منابع مشابه
n)-Approximation Algorithm For Directed Sparsest Cut
We give an O( √ n)-approximation algorithm for the Sparsest Cut Problem on directed graphs. A näıve reduction from Sparsest Cut to Minimum Multicut would only give an approximation ratio of O( √ n log D), where D is the sum of the demands. We obtain the improvement using a novel LP-rounding method for fractional Sparsest Cut, the dual of Maximum Concurrent Flow.
متن کاملTransitive-Closure Spanners of the Hypercube and the Hypergrid
Given a directed graph G = (V,E) and an integer k ≥ 1, a k-transitive-closure-spanner (k-TCspanner) of G is a directed graph H = (V,EH) that has (1) the same transitive-closure as G and (2) diameter at most k. Transitive-closure spanners were introduced in [7] as a common abstraction for applications in access control, property testing and data structures. In this work we study the number of ed...
متن کاملCut-Matching Games on Directed Graphs
We give O(log n)-approximation algorithm based on the cut-matching framework of [10, 13, 14] for the computing the sparsest cut on directed graphs. Our algorithm uses only O(log n) single commodity max-flow computations and thus breaks the multicommodity-flow barrier for computing the sparsest cut on directed graphs.
متن کامل8.1 Balanced Cut
In the last lecture, we described an O(log k logD)-approximation algorithm for Sparsest Cut, where k is the number of terminal pairs and D is the total requirement. Today we will describe an application of Sparsest Cut to the Balanced Cut problem. We will then develop an O(log k)approximation algorithm for Sparsest Cut, due to Linial, London, and Rabinovich [4], using metric embeddings techniqu...
متن کاملApproximating Non-Uniform Sparsest Cut Via Generalized Spectra
We give an approximation algorithm for non-uniform sparsest cut with the following guarantee: For any ε, δ ∈ (0, 1), given cost and demand graphs with edge weights C,D : ( V 2 ) → R+ respectively, we can find a set T ⊆ V with C(T,V \T ) D(T,V \T ) at most 1+ε δ times the optimal non-uniform sparsest cut value, in time 2 poly(n) provided λr ≥ Φ∗/(1 − δ). Here λr is the r’th smallest generalized ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2011