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Bayesian Nonlinear Support Vector Machines for Big Data by Wenzel, Florian; Galy-Fajou, Theo; Deutsch, Matthaeus; Kloft, Marius is a scholarly article available to read on EtoBox.

What is Bayesian Nonlinear Support Vector Machines for Big Data about?

We propose a fast inference method for Bayesian nonlinear support vector machines that leverages stochastic variational inference and inducing points. Our experiments show that the proposed method is faster than competing Bayesian approaches and scales easily to millions of data points. It provides additional features over frequentist competitors such as accurate predictive uncertainty estimates and automatic hyperparameter search.

Author

Wenzel, Florian; Galy-Fajou, Theo; Deutsch, Matthaeus; Kloft, Marius

Published

2017

Language

EN