The weighted majority algorithm
Information and Computation
Game theory, on-line prediction and boosting
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
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Competitive auctions and digital goods
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Competitive generalized auctions
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Incentive-compatible online auctions for digital goods
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The Nonstochastic Multiarmed Bandit Problem
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Online learning in online auctions
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Gambling in a rigged casino: The adversarial multi-armed bandit problem
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Truthful Mechanisms for One-Parameter Agents
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The Value of Knowing a Demand Curve: Bounds on Regret for Online Posted-Price Auctions
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Collusion-resistant mechanisms for single-parameter agents
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Mechanism Design via Machine Learning
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Anytime algorithms for multi-armed bandit problems
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SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
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Approximation algorithms and online mechanisms for item pricing
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Multi-unit auctions with unknown supply
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Adaptive mechanism design: a metalearning approach
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Online algorithms for market clearing
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Regret Minimization Under Partial Monitoring
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Dynamic pricing for impatient bidders
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Designing and learning optimal finite support auctions
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Mechanism design, machine learning, and pricing problems
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Reducing mechanism design to algorithm design via machine learning
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Stepwise randomized combinatorial auctions achieve revenue monotonicity
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The Design of Competitive Online Algorithms via a Primal: Dual Approach
Foundations and Trends® in Theoretical Computer Science
Setting discrete bid levels adaptively in repeated auctions
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Revenue monotonicity in combinatorial auctions
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The Balloon Popping Problem Revisited: Lower and Upper Bounds
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Dynamic pricing for impatient bidders
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Multi-parameter mechanism design and sequential posted pricing
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Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge
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On the competitive ratio of online sampling auctions
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Frequency capping in online advertising
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Truthful auctions with optimal profit
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Aggregating strategy for online auctions
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Prior-free auctions with ordered bidders
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Dynamic pricing with limited supply
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Toward a classification of finite partial-monitoring games
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On the Competitive Ratio of Online Sampling Auctions
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Truthful incentives in crowdsourcing tasks using regret minimization mechanisms
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Online pricing for bundles of multiple items
Journal of Global Optimization
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We consider the online auction problem proposed by Bar-Yossef, Hildrum, and Wu [4] in which an auctioneer is selling identical items to bidders arriving one at a time. We give an auction that achieves a constant factor of the optimal profit less an O(h) additive loss term, where h is the value of the highest bid. Furthermore, this auction does not require foreknowledge of the range of bidders' valuations. On both counts, this answers open questions from [4, 5]. We further improve on the results from [5] for the online posted-price problem by reducing their additive loss term from O(h log h log log h) to O(h log log h). Finally, we define the notion of an (offline) attribute auction for modeling the problem of auctioning items to consumers who are not a-priori indistinguishable. We apply our online auction solution to achieve good bounds for the attribute auction problem with 1-dimensional attributes.