Online Contention Resolution Schemes with Applications to Bayesian Selection Problems

We introduce a new rounding technique designed for online optimization problems, which is related to contention resolution schemes, initially introduced in the context of submodular function maximization. Our technique, we call schemes (OCRSs), applicable many selection including Bayesian selection, oblivious posted pricing mechanisms, and stochastic probing models. It allows handling wide set constraints shares strong properties offline schemes. In particular, OCRSs different constraint families can be combined obtain an OCRS their intersection. Moreover, approximately maximize functions settings consider. thus get broadly framework several improves on previous approaches terms types that handled, objective dealt with, assumptions strength adversary. Furthermore, resolve two open problems from literature; namely, present first constant-factor constrained price mechanism matroid algorithm weighted with deadlines.