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Collaborating Authors

 gredilla and titsia


Heteroscedastic Relevance Vector Machine

arXiv.org Machine Learning

In this work we propose a heteroscedastic generalization to RVM, a fast Bayesian framework for regression, based on some recent similar works. We use variational approximation and expectation propagation to tackle the problem. The work is still under progress and we are examining the results and comparing with the previous works.