A common approach for designing scalable algorithms for massive data sets is to distribute the computation across, say k, machines and process the data using limited communication between them. Aâ€¦ (More)

We investigate the problem of heterogeneous task assignment in crowdsourcing markets from the point of view of the requester, who has a collection of tasks. Workers arrive online one by one, and eachâ€¦ (More)

Recently, Czumaj et al. (arXiv 2017) presented a parallel (almost) 2-approximation algorithm for the maximum matching problem in only O ( (log logn) ) rounds of the massive parallel computation (MPC)â€¦ (More)

Motivated by an application in <i>kidney exchange</i>, we study the following <i>stochastic matching</i> problem: we are given a graph <i>G</i>(<i>V,E</i>) (not necessarily bipartite), where eachâ€¦ (More)

Motivated by the bus escape routing problem in printed circuit boards, we study the following rectangle escape problem: given a set S of n axis-aligned rectangles inside an axis-aligned rectangularâ€¦ (More)

In many learning settings, active/adaptive querying is possible, but the number of rounds of adaptivity is limited. We study the relationship between query complexity and adaptivity in identifyingâ€¦ (More)

A maximal independent set (MIS) can be maintained in an evolving m-edge graph by simply recomputing it from scratch in O(m) time after each update. But can it be maintained in time sublinear in m inâ€¦ (More)

Provisioning is a technique for avoiding repeated expensive computations in what-if analysis. Given a query, an analyst formulates k hypotheticals, each retaining some of the tuples of a databaseâ€¦ (More)

In the <i>stochastic matching</i> problem, we are given a general (not necessarily bipartite) graph <i>G</i>(<i>V</i>,<i>E</i>), where each edge in <i>E</i> is <i>realized</i> with some constantâ€¦ (More)