AdWords and Generalized On-line Matching
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Truthful auctions for pricing search keywords
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Budget optimization in search-based advertising auctions
Proceedings of the 8th ACM conference on Electronic commerce
Optimal delivery of sponsored search advertisements subject to budget constraints
Proceedings of the 8th ACM conference on Electronic commerce
Budget Constrained Bidding in Keyword Auctions and Online Knapsack Problems
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
The adwords problem: online keyword matching with budgeted bidders under random permutations
Proceedings of the 10th ACM conference on Electronic commerce
Online Stochastic Matching: Beating 1-1/e
FOCS '09 Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science
Online stochastic packing applied to display ad allocation
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction
FOCS '10 Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science
Near optimal online algorithms and fast approximation algorithms for resource allocation problems
Proceedings of the 12th ACM conference on Electronic commerce
Online Optimization with Uncertain Information
ACM Transactions on Algorithms (TALG)
Simultaneous approximations for adversarial and stochastic online budgeted allocation
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Online stochastic weighted matching: improved approximation algorithms
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
Asymptotically optimal algorithm for stochastic adwords
Proceedings of the 13th ACM Conference on Electronic Commerce
Advertisement allocation for generalized second-pricing schemes
Operations Research Letters
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In Internet ad auctions, search engines often throttle budget constrained advertisers so as to spread their spends across the specified time period. Such policies are known as budget smoothing policies. In this paper, we perform a principled, game-theoretic study of what the outcome of an ideal budget smoothing algorithm should be. In particular, we propose the notion of regret-free budget smoothing policies whose outcomes throttle each advertiser optimally, given the participation of the other advertisers. We show that regret-free budget smoothing policies always exist, and in the case of single slot auctions we can give a polynomial time smoothing algorithm. Inspired by the existence proof, we design a heuristic for budget smoothing which performs considerably better than existing benchmark heuristics.