Over the last decade, there has been considerable interest in designing algorithms for
processing massive graphs in the data stream model. The original motivation was two-fold …

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 …

We consider the problem of maximizing a nonnegative submodular set function f: 2^ N →
R^+ f: 2 N→ R+ subject to ap-matchoid constraint in the single-pass streaming setting …

We introduce a fully online model of maximum cardinality matching in which all vertices
arrive online. On the arrival of a vertex, its incident edges to previously-arrived vertices are …

Submodular function maximization has been studied extensively in recent years under
various constraints and models. The problem plays a major role in various disciplines. We …

In this paper, we develop the first one-pass streaming algorithm for submodular
maximization that does not evaluate the entire stream even once. By carefully subsampling …

We present a simple deterministic single-pass (2+ ε)-approximation algorithm for the
maximum weight matching problem in the semi-streaming model. This improves on the …

Abstract We present a (4+ epsilon) approximation algorithm for weighted graph matching
which applies in the semistreaming, sliding window, and MapReduce models; this single …

We introduce a fully online model of maximum cardinality matching in which all vertices
arrive online. On the arrival of a vertex, its incident edges to previously arrived vertices are …

Submodular maximization under matroid and cardinality constraints are classical problems
with a wide range of applications in machine learning, auction theory, and combinatorial …