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» Learning and Generalization with the Information Bottleneck
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ICML
2008
IEEE
16 years 7 months ago
Exploration scavenging
We examine the problem of evaluating a policy in the contextual bandit setting using only observations collected during the execution of another policy. We show that policy evalua...
John Langford, Alexander L. Strehl, Jennifer Wortm...
ICSE
2008
IEEE-ACM
16 years 7 months ago
Best practices in extreme programming course design
Teaching (and therefore learning) eXtreme Programming (XP) in a university setting is difficult because of course time limitations and the soft nature of XP that requires first-ha...
Kai Stapel, Daniel Lübke, Eric Knauss
WWW
2009
ACM
16 years 7 months ago
Predicting click through rate for job listings
Click Through Rate (CTR) is an important metric for ad systems, job portals, recommendation systems. CTR impacts publisher's revenue, advertiser's bid amounts in "p...
Manish S. Gupta
WWW
2008
ACM
16 years 7 months ago
Automatically refining the wikipedia infobox ontology
The combined efforts of human volunteers have recently extracted numerous facts from Wikipedia, storing them as machine-harvestable object-attribute-value triples in Wikipedia inf...
Fei Wu, Daniel S. Weld
WWW
2007
ACM
16 years 7 months ago
Predicting clicks: estimating the click-through rate for new ads
Search engine advertising has become a significant element of the Web browsing experience. Choosing the right ads for the query and the order in which they are displayed greatly a...
Matthew Richardson, Ewa Dominowska, Robert Ragno