
On the cut dimension of a graph
Let G = (V,w) be a weighted undirected graph with m edges. The cut dimen...
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Optimal Lower Bounds for Sketching Graph Cuts
We study the space complexity of sketching cuts and Laplacian quadratic ...
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Improved Lower Bound for Competitive Graph Exploration
We give an improved lower bound of 10/3 on the competitive ratio for the...
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An FPT algorithm for Matching Cut
In an undirected graph, a matching cut is an edge cut which is also a ma...
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On constant multicommodity flowcut gaps for directed minorfree graphs
The multicommodity flowcut gap is a fundamental parameter that affects...
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Quantum Lower Bounds for 2DGrid and Dyck Language
We show quantum lower bounds for two problems. First, we consider the pr...
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Quantum Lower and Upper Bounds for 2DGrid and Dyck Language
We study the quantum query complexity of two problems. First, we consi...
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Sparsification of Balanced Directed Graphs
Sparsification, where the cut values of an input graph are approximately preserved by a sparse graph (called a cut sparsifier) or a succinct data structure (called a cut sketch), has been an influential tool in graph algorithms. But, this tool is restricted to undirected graphs, because some directed graphs are known to not admit sparsification. Such examples, however, are structurally very dissimilar to undirected graphs in that they exhibit highly unbalanced cuts. This motivates us to ask: can we sparsify a balanced digraph? To make this question concrete, we define balance β of a digraph as the maximum ratio of the cut value in the two directions (Ene et al., STOC 2016). We show the following results: ForAll Sparsification: If all cut values need to be simultaneously preserved (cf. Benczúr and Karger, STOC 1996), then we show that the size of the sparsifier (or even cut sketch) must scale linearly with β. The upper bound is a simple extension of sparsification of undirected graphs (formally stated recently in Ikeda and Tanigawa (WAOA 2018)), so our main contribution here is to show a matching lower bound. ForEach Sparsification: If each cut value needs to be individually preserved (Andoni et al., ITCS 2016), then the situation is more interesting. Here, we give a cut sketch whose size scales with √(β), thereby beating the linear lower bound above. We also show that this result is tight by exhibiting a matching lower bound of √(β) on "foreach" cut sketches. Our upper bounds work for general weighted graphs, while the lower bounds even hold for unweighted graphs with no parallel edges.
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