Matching, capturing allocation of items to unit-demand buyers, or tasks to workers, or pairs of
collaborators, is a central problem in economics. Indeed, the growing prevalence of …

Crowdsourcing is a computing paradigm where humans are actively involved in a
computing task, especially for tasks that are intrinsically easier for humans than for …

Matching is a classic problem with a rich history and a significant impact, both on the theory
of algorithms and in practice. Recently there has been a surge of interest in the online …

We introduce the abstract problem of rounding an unknown fractional bipartite b-matching x
revealed online (eg, output by an online fractional algorithm), exposed node-by-node on …

The classical analysis of online algorithms, due to its worst-case nature, can be quite
pessimistic when the input instance at hand is far from worst-case. Often this is not an issue …

In a seminal paper, Karp, Vazirani, and Vazirani show that a simple ranking algorithm
achieves a competitive ratio of 1-1/e for the online bipartite matching problem in the …

We give a simple proof that the ranking algorithm of Karp, Vazirani and Vazirani [KVV90] is 1-
1/e competitive for the online bipartite matching problem. The proof is via a randomized …

We introduce the online stochastic Convex Programming (CP) problem, a very general
version of stochastic online problems which allows arbitrary concave objectives and convex …

We consider the online bipartite matching problem in the unknown distribution input model.
We show that the Ranking algorithm of [KVV90] achieves a competitive ratio of at least …

We study online variants of weighted bipartite matching on graphs and hypergraphs. In our
model for online matching, the vertices on the right-hand side of a bipartite graph are given …