Hilbert space methods for reduced-rank Gaussian process regression (English)
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- New search for: Särkkä, Simo
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- https://orcid.org/0000-0002-7031-9354
- New search for: Solin, Arno
- Further information on Solin, Arno:
- https://orcid.org/0000-0002-0958-7886
- New search for: Särkkä, Simo
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In:
Statistics and Computing
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30
, 2
; 419-446
;
2019
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ISSN:
- Article (Journal) / Print
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Title:Hilbert space methods for reduced-rank Gaussian process regression
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Contributors:Solin, Arno ( author ) / Särkkä, Simo ( author )
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Published in:Statistics and Computing ; 30, 2 ; 419-446
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Publisher:
- New search for: Springer US
- New search for: Springer
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Place of publication:New York, NY
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Publication date:2019
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ISSN:
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ZDBID:
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DOI:
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Type of media:Article (Journal)
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Type of material:Print
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Language:English
- New search for: 31.73 / 54.76
- Further information on Basic classification
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Keywords:
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Classification:
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Source:
Table of contents – Volume 30, Issue 2
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 209
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Nonparametric self-exciting models for computer network trafficPrice-Williams, Matthew / Heard, Nicholas A. et al. | 2020
- 221
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Semiparametric bivariate modelling with flexible extremal dependenceLeonelli, Manuele / Gamerman, Dani et al. | 2020
- 237
-
Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experimentsGlaws, Andrew / Constantine, Paul G. / Cook, R. Dennis et al. | 2020
- 255
-
Weighted likelihood mixture modeling and model-based clusteringGreco, Luca / Agostinelli, Claudio et al. | 2020
- 279
-
Inference for L2-BoostingRügamer, David / Greven, Sonja et al. | 2020
- 291
-
MCEN: a method of simultaneous variable selection and clustering for high-dimensional multinomial regressionRen, Sheng / Kang, Emily L. / Lu, Jason L. et al. | 2020
- 305
-
Nudging the particle filterAkyildiz, Ömer Deniz / Míguez, Joaquín et al. | 2020
- 331
-
Marginal information for structure learningKim, Gang-Hoo / Kim, Sung-Ho et al. | 2020
- 351
-
Robust Bayesian model selection for variable clustering with the Gaussian graphical modelAndrade, Daniel / Takeda, Akiko / Fukumizu, Kenji et al. | 2020
- 377
-
Modified Hamiltonian Monte Carlo for Bayesian inferenceRadivojević, Tijana / Akhmatskaya, Elena et al. | 2020
- 405
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Timing observations of diffusionsJaveed, Aurya / Hooker, Giles et al. | 2020
- 419
-
Hilbert space methods for reduced-rank Gaussian process regressionSolin, Arno / Särkkä, Simo et al. | 2020
- 447
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Nonparametric estimation of probabilistic sensitivity measuresAntoniano-Villalobos, Isadora / Borgonovo, Emanuele / Lu, Xuefei et al. | 2020
- 469
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Estimation of relative risk for events on a linear networkMcSwiggan, Greg / Baddeley, Adrian / Nair, Gopalan et al. | 2020