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» Generation of Attributes for Learning Algorithms
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WINE
2005
Springer
136views Economy» more  WINE 2005»
14 years 2 months ago
Click Fraud Resistant Methods for Learning Click-Through Rates
Abstract. In pay-per-click online advertising systems like Google, Overture, or MSN, advertisers are charged for their ads only when a user clicks on the ad. While these systems ha...
Nicole Immorlica, Kamal Jain, Mohammad Mahdian, Ku...
TCS
2010
13 years 7 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...
DEXA
2011
Springer
234views Database» more  DEXA 2011»
12 years 9 months ago
Learning Top-k Transformation Rules
Record linkage identifies multiple records referring to the same entity even if they are not bit-wise identical. It is thus an essential technology for data integration and data c...
Sunanda Patro, Wei Wang
COLT
2005
Springer
14 years 2 months ago
Separating Models of Learning from Correlated and Uncorrelated Data
We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...
ML
2010
ACM
163views Machine Learning» more  ML 2010»
13 years 4 months ago
Classification with guaranteed probability of error
We introduce a general-purpose learning machine that we call the Guaranteed Error Machine, or GEM, and two learning algorithms, a real GEM algorithm and an ideal GEM algorithm. Th...
Marco C. Campi