arXiv Open Access 2013

Heteroscedastic Relevance Vector Machine

Daniel Khashabi Mojtaba Ziyadi Feng Liang

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Abstrak

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.

Topik & Kata Kunci

stat.ML cs.LG

Penulis (3)

Daniel Khashabi

Mojtaba Ziyadi

Feng Liang

Format Sitasi

APA MLA BibTeX

Khashabi, D., Ziyadi, M., Liang, F. (2013). Heteroscedastic Relevance Vector Machine. https://arxiv.org/abs/1301.2015

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2013
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓