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Found 4 papers, 0 papers with code
Strategically-Robust Learning Algorithms for Bidding in First-Price Auctions
Concretely, we show that our algorithms achieve $O(\sqrt{T})$ regret when the highest competing bids are generated adversarially, and show that no online algorithm can do better.
Robust Budget Pacing with a Single Sample
Given the inherent non-stationarity in an advertiser's value and also competing advertisers' values over time, a commonly used approach is to learn a target expenditure plan that specifies a target spend as a function of time, and then run a controller that tracks this plan.
Online Resource Allocation under Horizon Uncertainty
We go on to give a fast algorithm for computing a schedule of target consumption rates that leads to near-optimal performance in the unknown-horizon setting.
Single-Leg Revenue Management with Advice
Moreover, we provide an online algorithm that always achieves performance on this Pareto frontier.
