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» Learning Instance-Specific Predictive Models
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WWW
2009
ACM
14 years 9 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
BIOTECHNO
2008
IEEE
14 years 3 months ago
Combining Boundaries and Ratings from Multiple Observers for Predicting Lung Nodule Characteristics
We use the data collected by the Lung Image Database Consortium (LIDC) for modeling the radiologists’ nodule interpretations based on image content of the nodule by using decisi...
Ekarin Varutbangkul, Vesna Mitrovic, Daniela Stan ...
NIPS
2007
13 years 10 months ago
Multi-task Gaussian Process Prediction
In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features...
Edwin V. Bonilla, Kian Ming Chai, Christopher K. I...
CVPR
2012
IEEE
11 years 11 months ago
Weakly supervised structured output learning for semantic segmentation
We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
NIPS
2008
13 years 10 months ago
Structured ranking learning using cumulative distribution networks
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Jim C. Huang, Brendan J. Frey