Efficient modeling of latent information in supervised learning using Gaussian processes

Alvarez Lopez, M.A., Dai, Z. and Lawrence, N.D. (2017) Efficient modeling of latent information in supervised learning using Gaussian processes. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S. and Garnett, R., (eds.) Advances in Neural Information Processing Systems 30 (NIPS 2017) pre-proceedings. Advances in Neural Information Processing Systems (NIPS) 2017, 04-09 Dec 2017, Long Beach, CA. Massachusetts Institute of Technology Press .

Abstract

Metadata

Authors/Creators:
  • Alvarez Lopez, M.A.
  • Dai, Z.
  • Lawrence, N.D.
Copyright, Publisher and Additional Information: © 2017 Massachusetts Institute of Technology Press. This is an author produced version of a paper subsequently published in Advances in Neural Information Processing Systems 30 (NIPS 2017) pre-proceedings. Uploaded in accordance with the publisher's self-archiving policy.
Dates:
  • Accepted: 4 September 2017
  • Published (online): 16 November 2017
  • Published: 16 November 2017
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
FunderGrant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/N014162/1
Depositing User: Symplectic Sheffield
Date Deposited: 12 Jan 2018 16:38
Last Modified: 03 Apr 2019 12:43
Published Version: https://papers.nips.cc/paper/7098-efficient-modeli...
Status: Published
Publisher: Massachusetts Institute of Technology Press
Refereed: Yes

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