Beyond Classification -- Large-Scale Gaussian Process Inference and Uncertainty Prediction

TitleBeyond Classification -- Large-Scale Gaussian Process Inference and Uncertainty Prediction
Publication TypeMiscellaneous
Year of Publication2012
AuthorsFreytag, A., Rodner E., Bodesheim P., & Denzler J.
Other Numbers3366

Due to the massive (labeled) data available on the web, a tremendous interest inlarge-scale machine learning methods has emerged in the last years. Whereas,most of the work done in this new area of research focused on fast and efficientclassification algorithms, we show in this paper how other aspects of learning canalso be covered using massive datasets. The paper briefly presents techniquesallowing for utilizing the full posterior obtained from Gaussian process regression(predictive mean and variance) with tens of thousands of data points and withoutrelying on sparse approximation approaches. Experiments are done for activelearning and one-class classification showing the benefits in large-scale settings.


This work was partially funded by the Deutscher Akademischer Austausch Dienst (DAAD) through a postdoctoral fellowship.

Bibliographic Notes

Presented at the BigVision Workshop at the 26th Annual Conference on Neural Information Processing Systems (NIPS 2012), Lake Tahoe, Nevada

Abbreviated Authors

A. Freytag, E. Rodner, P. Bodesheim, and J. Denzler

ICSI Research Group


ICSI Publication Type

Talk or presentation