An optimal algorithm for on-line bipartite matching
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
Improvements to the Linear Programming Based Scheduling of Web Advertisements
Electronic Commerce Research
The adwords problem: online keyword matching with budgeted bidders under random permutations
Proceedings of the 10th ACM conference on Electronic commerce
Online allocation of display advertisements subject to advanced sales contracts
Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising
Bidding for Representative Allocations for Display Advertising
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Online Stochastic Matching: Beating 1-1/e
FOCS '09 Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science
Forecasting high-dimensional data
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Optimal online assignment with forecasts
Proceedings of the 11th ACM conference on Electronic commerce
Balanced allocation with succinct representation
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Commitment under uncertainty: two-stage stochastic matching problems
ICALP'07 Proceedings of the 34th international conference on Automata, Languages and Programming
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A large fraction of online display advertising is sold via guaranteed contracts: a publisher guarantees to the advertiser a certain number of user visits satisfying the targeting predicates of the contract. The publisher is then tasked with solving the ad serving problem ---given a user visit, which of the thousands of matching contracts should be displayed, so that by the expiration time every contract has obtained the requisite number of user visits. The challenges of the problem come from (1) the sheer size of the problem being solved, with tens of thousands of contracts and billions of user visits, (2) the unpredictability of user behavior, since these contracts are sold months ahead of time, when only a forecast of user visits is available and (3) the minute amount of resources available online, as an ad server must respond with a matching contract in a fraction of a second. We present a solution to the guaranteed delivery ad serving problem using compact allocation plans. These plans, computed offline, can be efficiently queried by the ad server during an ad call; they are small, using only O(1) space for contract; and are stateless, allowing for distributed serving without any central coordination. We evaluate this approach on a real set of user visits and guaranteed contracts and show that the compact allocation plans are an effective way of solving the guaranteed delivery ad serving problem.