Multi-task beta process sparse kernel machines

In this paper we propose a nonparametric extension to the sparse kernel machine using a beta process prior. The extended beta process sparse kernel machine (BPSKM) allows for a sparse model to be constructed from a set of training data. The recent research on beta process reveals elegant property of Bayesian conjugate prior which is utilized to derive a variational Bayes inference algorithm. The performance of the proposed algorithm has been investigated on both synthetic and real-life data sets.