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 …

With the rapid development of smartphones, spatial crowdsourcing platforms are getting
popular. A foundational research of spatial crowdsourcing is to allocate micro-tasks to …

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 a simple model of dynamic matching in networked markets, where agents
arrive and depart stochastically and the composition of the trade network depends …

We consider the problem of a search engine trying to assign a sequence of search keywords
to a set of competing bidders, each with a daily spending limit. The goal is to maximize the …

We study the online stochastic bipartite matching problem, in a form motivated by display ad
allocation on the Internet. In the online, but adversarial case, the celebrated result of Karp …

A natural optimization model that formulates many online resource allocation problems is
the online linear programming (LP) problem in which the constraint matrix is revealed …

Bipartite-matching markets pair agents on one side of a market with agents, items, or
contracts on the opposing side. Prior work addresses online bipartite-matching markets …

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 …

The popularity of Online To Offline (O2O) service platforms has spurred the need for online
task assignment in real-time spatial data, where streams of spatially distributed tasks and …