An Anomaly Detection Method for Spacecraft Using Relevance Vector Learning-Reference-Cited by-同舟云学术

An Anomaly Detection Method for Spacecraft Using Relevance Vector Learning

Published:2005 Issue: Volume: Page:785-790
ISSN:0302-9743
Container-title:Advances in Knowledge Discovery and Data Mining
language:
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Author:

Fujimaki Ryohei,Yairi Takehisa,Machida Kazuo

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11430919_92.pdf

Reference11 articles.

1. Faul, A.C., Tipping, M.E.: Analysis of Sparse Bayesian Learning. In: Dietterich, T.G., Becker, S., Ghahramanim, Z. (eds.) Advances in Neural Information Processing Systems, vol. 14, pp. 383–389. MIT Press, Cambridge (2002)

2. Bishop, C.M., Tipping, M.E.: Variational Relevance Vector Machines. In: Boutilier, C., Goldszmidt, M. (eds.) Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence, pp. 46–53. Morgan Kaufmann, San Francisco (2000)

3. Lecture Notes in Computer Science;K.-R. Muller,1997

4. Tipping, M.E.: Sparse Bayesian Learning and the Relevance Vector Machinem. Journal of Machine Learning Research 1, 211–244 (2001)

5. Tipping, M.E.: The Relevance Vector Machine. In: Solla, S.A., Leen, T.K., Muller, K.-R. (eds.) Advances in Neural Information Processing Systems, vol. 12, pp. 652–658. MIT Press, Cambridge (2000)

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