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EOR
2007
85views more  EOR 2007»
13 years 9 months ago
Reject inference, augmentation, and sample selection
Many researchers see the need for reject inference in credit scoring models to come from a sample selection problem whereby a missing variable results in omitted variable bias. Al...
John Banasik, Jonathan Crook
WSDM
2010
ACM
254views Data Mining» more  WSDM 2010»
14 years 6 months ago
Learning Influence Probabilities In Social Networks
Recently, there has been tremendous interest in the phenomenon of influence propagation in social networks. The studies in this area assume they have as input to their problems a ...
Amit Goyal 0002, Francesco Bonchi, Laks V. S. Laks...
KDD
2009
ACM
172views Data Mining» more  KDD 2009»
14 years 1 months ago
Learning dynamic temporal graphs for oil-production equipment monitoring system
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen
NIPS
2008
13 years 10 months ago
Unifying the Sensory and Motor Components of Sensorimotor Adaptation
Adaptation of visually guided reaching movements in novel visuomotor environments (e.g. wearing prism goggles) comprises not only motor adaptation but also substantial sensory ada...
Adrian Haith, Carl P. T. Jackson, R. Chris Miall, ...
UAI
2008
13 years 10 months ago
Learning Arithmetic Circuits
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
Daniel Lowd, Pedro Domingos