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 study the classic mathematical economics problem of Bayesian optimal mechanism
design where a principal aims to optimize expected revenue when allocating resources to …

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 …

Consider a gambler who observes a sequence of independent, non-negative random
numbers and is allowed to stop the sequence at any time, claiming a reward equal to the …

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 study the following vertex-weighted online bipartite matching problem: G (U, V, E) is a
bipartite graph. The vertices in U have weights and are known ahead of time, while the …

Inspired by online ad allocation, we study online stochastic packing integer programs from
theoretical and practical standpoints. We first present a near-optimal online algorithm for a …

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 …