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  It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals

Rakitsch, B., Lippert, C., Borgwardt, K., & Stegle, O. (2014). It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals. In C. J. Burges, L. Bottou, M. Welling, Z. Ghahramani, & K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems 26 (pp. 1468-1476). Red Hook, NY: Curran Associates, Inc. Retrieved from https://papers.nips.cc/paper/2013/hash/59c33016884a62116be975a9bb8257e3-Abstract.html.

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 Creators:
Rakitsch, Barbara1, Author           
Lippert, Christoph2, Author
Borgwardt, Karsten1, 2, Author           
Stegle, Oliver2, Author
Affiliations:
1Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497664              
2External Organizations, ou_persistent22              

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Free keywords: Forschungsgruppe Borgwardt
 Abstract: -

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Language(s): eng - English
 Dates: 20132014-04
 Publication Status: Issued
 Pages: 9
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Degree: -

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Title: 27th Annual Conference on Neural Information Processing Systems (NIPS 2013)
Place of Event: Lake Tahoe, NV
Start-/End Date: 2013-12-05 - 2013-12-10

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Title: Advances in Neural Information Processing Systems 26
  Subtitle : 27th Annual Conference on Neural Information Processing Systems 2013
Source Genre: Proceedings
 Creator(s):
Burges, C. J.1, Editor
Bottou, L.1, Editor
Welling, M.1, Editor
Ghahramani, Z.1, Editor
Weinberger, K. Q.1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Red Hook, NY : Curran Associates, Inc.
Pages: - Volume / Issue: 2 Sequence Number: - Start / End Page: 1468 - 1476 Identifier: URI: https://papers.nips.cc/paper/2013
ISBN: 978-1-63266-024-4