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We study the problem of finding a maximum matching in a graph given by an input stream listing its edges in some arbitrary order, where the quantity to be maximized is given by a monotone submodular function on subsets of edges. This problem, which we call maximum submodular-function matching (MSM), is a natural generalization of maximum weight matching… (More)

We consider the maximum matching problem in the semi-streaming model formalized by Feigenbaum et al. [13] that is inspired by giant graphs of today. As our main result, we give a two-pass (1/2 + 1/16)-approximation algorithm for bipartite/triangle-free graphs and a two-pass (1/2 + 1/32)-approximation algorithm for general graphs; these improve the ratios of… (More)

We develop a paradigm for studying multi-player deterministic communication, based on a novel combinatorial concept that we call a strong fooling set. Our paradigm leads to optimal lower bounds on the per-player communication required for solving multi-player EQUALITY problems in a private-message setting. This in turn gives a very strong—O(1) versus Ω(n)—… (More)

- Sagar Kale
- ArXiv
- 2012

Submodular functions have many applications. Matchings have many applications. The bitext word alignment problem can be modeled as the problem of maximizing a nonnegative, monotone, submodular function constrained to matchings in a complete bipartite graph where each vertex corresponds to a word in the two input sentences and each edge represents a… (More)

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