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 …

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 …

Employment outcomes of resettled refugees depend strongly on where they are placed
inside the host country. While the US sets refugee capacities for communities on an annual …

We study the power of multiple choices in online stochastic matching. Despite a long line of
research, existing algorithms still only consider two choices of offline neighbors for each …

We study the online stochastic matching problem. Consider a bipartite graph with offline
vertices on one side, and with iid online vertices on the other side. The offline vertices and …

Three decades ago, Karp, Vazirani, and Vazirani (STOC 1990) defined the online matching
problem and gave an optimal (1-1/e)-competitive (about 0.632) algorithm. Fifteen years later …

Abstract Mehta and Panigrahi (2012) proposed Online Matching with Stochastic Rewards,
which generalizes the Online Bipartite Matching problem of Karp, Vazirani, and Vazirani …

Nearly three decades ago, Bar-Noy, Motwani and Naor showed that no online edge-coloring
algorithm can edge color a graph optimally. Indeed, their work, titled" the greedy algorithm is …

The design of online policies for stochastic matching and revenue management settings is
usually bound by the Bayesian prior that the demand process is formed by a fixed-length …

We study streaming submodular maximization subject to matching/b-matching constraints
(MSM/MSbM), and present improved upper and lower bounds for these problems. On the …