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IM
2008
14 years 10 months ago
The Structure of Geographical Threshold Graphs
We analyze the structure of random graphs generated by the geographical threshold model. The model is a generalization of random geometric graphs. Nodes are distributed in space, a...
Milan Bradonjic, Aric A. Hagberg, Allon G. Percus
CORR
2007
Springer
112views Education» more  CORR 2007»
14 years 10 months ago
Learning from compressed observations
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
Maxim Raginsky
MKTSCI
2010
100views more  MKTSCI 2010»
14 years 8 months ago
A Model for Trade-Up and Change in Considered Brands
A common theme in the marketing literature is the acquisition and retention of customers as they trade-up from inexpensive, introductory offerings to those of higher quality. We e...
Greg M. Allenby, Mark J. Garratt, Peter E. Rossi
ACL
2009
14 years 7 months ago
Learning with Annotation Noise
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...
Eyal Beigman, Beata Beigman Klebanov
AAAI
2011
13 years 10 months ago
Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
Marion Neumann, Babak Ahmadi, Kristian Kersting