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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. M., & Stegle, O. (2013). It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals. In C. Burges, L. Bottou, M. Welling, Z. Ghahramani, & K. Weinberger (Eds.), Advances in Neural Information Processing Systems 26 (NIPS 2013) (pp. 1466-1474). Retrieved from http://papers.nips.cc/paper/5089-it-is-all-in-the-noise-efficient-multi-task-gaussian-process-inference-with-structured-residuals.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0015-3A26-A Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0018-A3F2-7
Genre: Conference Paper

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 Creators:
Rakitsch, Barbara1, Author           
Lippert, Christoph, Author
Borgwardt, Karsten M.1, Author           
Stegle, Oliver, Author
Affiliations:
1Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497664              

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Free keywords: Forschungsgruppe Borgwardt
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 Dates: 2013
 Publication Status: Published online
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 Identifiers: BibTex Citekey: NIPS2013_5089
URI: http://papers.nips.cc/paper/5089-it-is-all-in-the-noise-efficient-multi-task-gaussian-process-inference-with-structured-residuals
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Title: Neural Information Processing Systems (NIPS) 2013
Place of Event: Lake Tahoe, NV, USA
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Title: Advances in Neural Information Processing Systems 26 (NIPS 2013)
Source Genre: Proceedings
 Creator(s):
Burges, C.J.C., Editor
Bottou, L., Editor
Welling, M., Editor
Ghahramani, Z., Editor
Weinberger, K.Q., Editor
Affiliations:
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Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1466 - 1474 Identifier: URI: http://papers.nips.cc/book/advances-in-neural-information-processing-systems-26-2013