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Learning in Repeated Auctions with Budgets: Regret Minimization and Equilibrium · Study

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ArticleLearning in Repeated Auctions with Budgets: Regret Minimization and Equilibrium

Santiago Balseiro2017

OA

Articlegreen2017

Learning in Repeated Auctions with Budgets: Regret Minimization and Equilibrium

Santiago Balseiro · Yonatan Gur

151 citations·0/0 files stored·Management Science

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Auction Theory and Applications Advanced Bandit Algorithms Research Optimization and Search Problems

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References

2006Prediction, Learning, and Games 1965Existence and Uniqueness of Equilibrium Points for Concave N-Person Games 2004The Theory and Practice of Revenue Management 2003Stochastic Approximation and Recursive Algorithms and Applications 2003Online convex programming and generalized infinitesimal gradient ascent 2012Online Learning and Online Convex Optimization 1952Contributions to the Theory of Games 2011Online Learning and Online Convex Optimization

Cited by

2015Learning and Efficiency in Games with Dynamic Population 2020Reinforcement Mechanism Design: With Applications to Dynamic Pricing in Sponsored Search Auctions 2021Multiplicative Pacing Equilibria in Auction Markets 2021Online Linear Programming: Dual Convergence, New Algorithms, and Regret Bounds 2021Towards Efficient Auctions in an Auto-bidding World 2022Cold Start to Improve Market Thickness on Online Advertising Platforms: Data-Driven Algorithms and Field Experiments

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Year2017

Typearticle

Published2017-01-01

VenueManagement Science

ISSN-L0025-1909

Languageen

Citations151

Files0 public / 0

ShelfAuction Theory and Applications

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doi10.1287/mnsc.2018.3174

openalex_workW2966080558

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2018Learning to Bid Without Knowing your Value

2024Investor Regret and Stock Returns