1,752,370 research outputs found
Approximation Algorithms for Hypergraph Small Set Expansion and Small Set Vertex Expansion
The expansion of a hypergraph, a natural extension of the notion of expansion
in graphs, is defined as the minimum over all cuts in the hypergraph of the
ratio of the number of the hyperedges cut to the size of the smaller side of
the cut. We study the Hypergraph Small Set Expansion problem, which, for a
parameter , asks to compute the cut having the least
expansion while having at most fraction of the vertices on the smaller
side of the cut. We present two algorithms. Our first algorithm gives an
approximation. The second algorithm finds
a set with expansion in a --uniform hypergraph with maximum degree
(where is the expansion of the optimal solution).
Using these results, we also obtain algorithms for the Small Set Vertex
Expansion problem: we get an
approximation algorithm and an algorithm that finds a set with vertex expansion
(where is the vertex expansion of the optimal
solution).
For , Hypergraph Small Set Expansion is equivalent to the
hypergraph expansion problem. In this case, our approximation factor of
for expansion in hypergraphs matches the corresponding
approximation factor for expansion in graphs due to ARV
On approximation of homeomorphisms of a Cantor set
We continue to study topological properties of the group Homeo(X) of all
homeomorphisms of a Cantor set X with respect to the uniform topology tau,
which was started in the paper (S. Bezuglyi, A.H. Dooley, and J. Kwiatkowski,
Topologies on the group of homeomorphisms of a Cantor set, ArXiv e-print
math.DS/0410507, 2004). We prove that the set of periodic homeomorphisms is
tau-dense in Homeo(X) and deduce from this result that the topological group
(Homeo(X), tau) has the Rokhlin property, i.e., there exists a homeomorphism
whose conjugate class is tau-dense in Homeo(X). We also show that for any
homeomorphism T the topological full group [[T]] is tau-dense in the full group
[T].Comment: 12 pages: typos fixe
Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class
We develop a framework for generalizing approximation algorithms from the structural graph algorithm literature so that they apply to graphs somewhat close to that class (a scenario we expect is common when working with real-world networks) while still guaranteeing approximation ratios. The idea is to edit a given graph via vertex- or edge-deletions to put the graph into an algorithmically tractable class, apply known approximation algorithms for that class, and then lift the solution to apply to the original graph. We give a general characterization of when an optimization problem is amenable to this approach, and show that it includes many well-studied graph problems, such as Independent Set, Vertex Cover, Feedback Vertex Set, Minimum Maximal Matching, Chromatic Number, (l-)Dominating Set, Edge (l-)Dominating Set, and Connected Dominating Set.
To enable this framework, we develop new editing algorithms that find the approximately-fewest edits required to bring a given graph into one of a few important graph classes (in some cases these are bicriteria algorithms which simultaneously approximate both the number of editing operations and the target parameter of the family). For bounded degeneracy, we obtain an O(r log{n})-approximation and a bicriteria (4,4)-approximation which also extends to a smoother bicriteria trade-off. For bounded treewidth, we obtain a bicriteria (O(log^{1.5} n), O(sqrt{log w}))-approximation, and for bounded pathwidth, we obtain a bicriteria (O(log^{1.5} n), O(sqrt{log w} * log n))-approximation. For treedepth 2 (related to bounded expansion), we obtain a 4-approximation. We also prove complementary hardness-of-approximation results assuming P != NP: in particular, these problems are all log-factor inapproximable, except the last which is not approximable below some constant factor 2 (assuming UGC)
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