A dynamic learning algorithm for online matching problems with concave returns

•We consider the online matching problem with concave returns. It is the core model for ad allocation.•We propose a dynamic learning algorithm that achieves near-optimal performance for this problem.•Our approach is primal-dual based. We overcome the difficulty that arises due to the nonlinearity.•W...

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