Learning to Bid in Repeated Second-Price Auctions with Dynamic Values and Aggregated Feedback

ArXi:2605.28133v1 Announce Type: new We study the problem of learning to bid when the bidder's value is dynamic, i.e., when the current value depends on past outcomes. Specifically, we consider a bidder participating in repeated second-price auctions whose value depends on the time elapsed since their last successful bid, with auctions arriving in continuous time and only aggregated feedback revealed at the end of the horizon.