Adaptive limited-supply online auctions
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Online auctions with re-usable goods
Proceedings of the 6th ACM conference on Electronic commerce
Online ascending auctions for gradually expiring items
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Anytime algorithms for multi-armed bandit problems
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Learning algorithms for online principal-agent problems (and selling goods online)
ICML '06 Proceedings of the 23rd international conference on Machine learning
Regret Minimization Under Partial Monitoring
Mathematics of Operations Research
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Designing and learning optimal finite support auctions
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Noisy binary search and its applications
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Automated online mechanism design and prophet inequalities
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Dynamic Pricing with a Prior on Market Response
Operations Research
Multi-parameter mechanism design and sequential posted pricing
Proceedings of the forty-second ACM symposium on Theory of computing
Algorithms and theory of computation handbook
Learning the demand curve in posted-price digital goods auctions
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Dynamic pricing with limited supply
Proceedings of the 13th ACM Conference on Electronic Commerce
Learning on a budget: posted price mechanisms for online procurement
Proceedings of the 13th ACM Conference on Electronic Commerce
Dynamic Pricing Under a General Parametric Choice Model
Operations Research
Toward a classification of finite partial-monitoring games
Theoretical Computer Science
Truthful incentives in crowdsourcing tasks using regret minimization mechanisms
Proceedings of the 22nd international conference on World Wide Web
Sequential decision making with vector outcomes
Proceedings of the 5th conference on Innovations in theoretical computer science
Online learning for auction mechanism in bandit setting
Decision Support Systems
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We consider price-setting algorithms for a simple market in which a seller has an unlimited supply of identical copies of some good, and interacts sequentially with a pool of n buyers, each of whom wants at most one copy of the good. In each transaction, the seller offers a price between 0 and 1, and the buyer decides whether or not to buy, by comparing the offered price to his privately-held valuation for the good. The price offered to a given buyer may be influenced by the outcomes of prior transactions, but each individual buyer participates only once.In this setting, what is the value of knowing the demand curve? In other words, how much revenue can an uninformed seller expect to obtain, relative to a seller with prior information about the buyers' valuations? The answer depends on how the buyers' valuations are modeled. We analyze three cases 驴 identical, random, and worst-case valuations 驴 in each case deriving upper and lower bounds which match within a sublogarithmic factor.