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DBLP
Article . 2011
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Online algorithms with stochastic input

Authors: Nikhil R. Devanur;

Online algorithms with stochastic input

Abstract

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 simplifications that ignore certain aspects of the actual way this allocation is done. For instance, it assumes a "first-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.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Top 10%
Average
bronze