Online Algorithms with Stochastic Input NIKHIL R. DEVANUR Microsoft Research Categories and Subject Descriptors: F.2.m [ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY]: Miscellaneous General Terms: Algorithms Additional Key Words and Phrases: Online, Matching, Adwords, Learning, Random Permutation 1. INTRODUCTION The design and analysis of online algorithms, where the input to the algorithm is revealed over time and the algorithm has to make decisions immediately without knowing the future input, has received a revived interest in the last few years primarily due to their application to online advertising. The canonical problem is the Adwords problem, which is motivated by the problem of optimally allocating ad slots on search queries to budget constrained advertisers. It involves simpli cations that ignore certain aspects of the actual way this allocation is done. For instance, it assumes a rst-price pay-per-impression scheme, ignoring the game theoretic aspects, and considers only one slot per query. To be precise, the Adwords problem is as follows. The Adwords problem: Input: n = number of advertisers m = number of queries i = 1..n, Bi = Budget of advertiser i For j = 1..m Input: i = 1..n, bij = bid of advertiser i for query
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Online algorithms with stochastic input
Devanur, Nikhil R.
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, Volume 10 (2)
Association for Computing Machinery – Jun 1, 2011
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