Journal article
A Sparse Gaussian Process Framework for Photometric Redshift Estimation
- Abstract:
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Accurate photometric redshifts are a lynchpin for many future experiments to pin down the cosmological model and for studies of galaxy evolution. In this study, a novel sparse regression framework for photometric redshift estimation is presented. Simulated and real data from SDSS DR12 were used to train and test the proposed models. We show that approaches which include careful data preparation and model design offer a significant improvement in comparison with several competing machine learn...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 524.2KB, Terms of use)
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- Publisher copy:
- 10.1093/mnras/stv2425
Authors
Bibliographic Details
- Publisher:
- Oxford University Press
- Journal:
- Monthly Notices of the Royal Astronomical Society More from this journal
- Publication date:
- 2015-11-01
- DOI:
- ISSN:
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1365-2966
Item Description
- Keywords:
- Pubs id:
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pubs:570368
- UUID:
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uuid:7097dab7-448a-4835-ac06-285ce6b0eaa0
- Local pid:
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pubs:570368
- Source identifiers:
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570368
- Deposit date:
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2015-12-10
Terms of use
- Copyright holder:
- Almosallam et al
- Copyright date:
- 2015
- Notes:
- © 2015 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society
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