Risk criteria in a stochastic knapsack problem
Operations Research
Allocating Bandwidth for Bursty Connections
SIAM Journal on Computing
The Sample Average Approximation Method for Stochastic Discrete Optimization
SIAM Journal on Optimization
Stochastic Load Balancing and Related Problems
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Approximating the Stochastic Knapsack Problem: The Benefit of Adaptivity
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Multi-unit auctions with budget-constrained bidders
Proceedings of the 6th ACM conference on Electronic commerce
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
An adaptive algorithm for selecting profitable keywords for search-based advertising services
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Dynamics of bid optimization in online advertisement auctions
Proceedings of the 16th international conference on World Wide Web
Budget optimization in search-based advertising auctions
Proceedings of the 8th ACM conference on Electronic commerce
Allocating online advertisement space with unreliable estimates
Proceedings of the 8th ACM conference on Electronic commerce
Budget constrained bidding in keyword auctions and online knapsack problems
Proceedings of the 17th international conference on World Wide Web
Sampling bounds for stochastic optimization
APPROX'05/RANDOM'05 Proceedings of the 8th international workshop on Approximation, Randomization and Combinatorial Optimization Problems, and Proceedings of the 9th international conference on Randamization and Computation: algorithms and techniques
Algorithm for stochastic multiple-choice knapsack problem and application to keywords bidding
Proceedings of the 17th international conference on World Wide Web
A Cascade Model for Externalities in Sponsored Search
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
Bid optimization for broad match ad auctions
Proceedings of the 18th international conference on World wide web
Mining advertiser-specific user behavior using adfactors
Proceedings of the 19th international conference on World wide web
Random effects model for estimating effectiveness of advertising in online marketplaces
Expert Systems with Applications: An International Journal
Sponsored search auctions: an overview of research with emphasis on game theoretic aspects
Electronic Commerce Research
Budget optimization for online campaigns with positive carryover effects
WINE'12 Proceedings of the 8th international conference on Internet and Network Economics
Machine learning with operational costs
The Journal of Machine Learning Research
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Internet search companies sell advertisement slots based on users' search queries via an auction. Advertisers have to determine how to place bids on the keywords of their interest in order to maximize their return for a given budget: this is the budget optimization problem. The solution depends on the distribution of future queries. In this paper, we formulate stochastic versions of the budget optimization problem based on natural probabilistic models of distribution over future queries, and address two questions that arise. Evaluation. Given a solution, can we evaluate the expected value of the objective function? Optimization. Can we find a solution that maximizes the objective function in expectation? Our main results are approximation and complexity results for these two problems in our three stochastic models. In particular, our algorithmic results show that simple prefix strategies that bid on all cheap keywords up to some level are either optimal or good approximations for many cases; we show other cases to be NP-hard.