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 …

Privacy-preserving online multi-task assignment is a crucial aspect of spatial crowdsensing
on untrusted platforms, where multiple real-time tasks are allocated to appropriate workers …

We provide prophet inequality algorithms for online weighted matching in general (non-
bipartite) graphs, under two well-studied arrival models, namely edge arrival and vertex …

Online bipartite matching is one of the most fundamental problems in the online algorithms
literature. Karp, Vazirani, and Vazirani (STOC 1990) gave an elegant algorithm for …

Motivated by applications from ride-sharing and kidney exchange, we study the problem of
matching agents who arrive at a marketplace over time and leave after d time periods …

Motivated by centralized matching markets, we study an online stochastic matching problem
on edge-weighted graphs, where the agents' arrivals and abandonments are stochastic and …

The online matching problem was introduced by Karp, Vazirani and Vazirani nearly three
decades ago. In that seminal work, they studied this problem in bipartite graphs with vertices …

We study maximum matchings in fully dynamic graphs, which are graphs that undergo both
edge insertions and deletions. Our focus is on algorithms that estimate the size of maximum …

The bipartite matching problem in the online and streaming settings has received a lot of
attention recently. The classical vertex arrival setting, for which the celebrated Karp, Vazirani …

We consider Bayesian online selection problem of a matching in bipartite graphs, ie, online
weighted matching problem with edge arrivals where online algorithm knows distributions of …