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JMLR
2010
132views more  JMLR 2010»
13 years 4 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
ECCV
2008
Springer
14 years 12 months ago
Learning to Localize Objects with Structured Output Regression
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Matthew B. Blaschko, Christoph H. Lampert
WWW
2009
ACM
14 years 10 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
IEEECIT
2010
IEEE
13 years 8 months ago
A Learning Spectrum Hole Prediction Model for Cognitive Radio Systems
—In this paper, we present a new spectrum-hole prediction model for cognitive radio (CR) systems based on the IEEE 802.11 wireless local areas networks. We have also analyzed the...
Zhigang Wen, Chunxiao Fan, Xiaoying Zhang, Yuexin ...
ISIPTA
2005
IEEE
162views Mathematics» more  ISIPTA 2005»
14 years 3 months ago
Learning from multinomial data: a nonparametric predictive alternative to the Imprecise Dirichlet Model
A new model for learning from multinomial data has recently been developed, giving predictive inferences in the form of lower and upper probabilities for a future observation. Apa...
Frank P. A. Coolen, Thomas Augustin