Primal-Dual Algorithms with Predictions for Online Bounded Allocation and Ad-Auctions Problems

arXiv:2402.08701v1 Announce Type: cross
Abstract: Matching problems have been widely studied in the research community, especially Ad-Auctions with many applications ranging from network design to advertising. Following the various advancements in machine learning, one natural question is whether classical algorithms can benefit from machine learning and obtain better-quality solutions. Even a small percentage of performance improvement in matching problems could result in significant gains for the studied use cases. For example, the network throughput or the revenue of Ad-Auctions can …

abstract advertising algorithms applications arxiv benefit community cs.dm cs.ds cs.gt cs.lg design machine machine learning natural network predictions primal quality question research research community solutions type