Hybrid discriminative-generative approach with Gaussian processes

Data Science Institute

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

Hybrid discriminative-generative approach with Gaussian processes. / Andrade-Pacheco, Ricardo; Hensman, James; Zwießele, Max et al.
In: Proceedings of Machine Learning Research, Vol. 33, 2014, p. 47-56.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Andrade-Pacheco, R, Hensman, J, Zwießele, M & Lawrence, ND 2014, 'Hybrid discriminative-generative approach with Gaussian processes', Proceedings of Machine Learning Research, vol. 33, pp. 47-56. <http://www.jmlr.org/proceedings/papers/v33/andradepacheco14.html>

APA

Andrade-Pacheco, R., Hensman, J., Zwießele, M., & Lawrence, N. D. (2014). Hybrid discriminative-generative approach with Gaussian processes. Proceedings of Machine Learning Research, 33, 47-56. http://www.jmlr.org/proceedings/papers/v33/andradepacheco14.html

Vancouver

Andrade-Pacheco R, Hensman J, Zwießele M, Lawrence ND. Hybrid discriminative-generative approach with Gaussian processes. Proceedings of Machine Learning Research. 2014;33:47-56.

Author

Andrade-Pacheco, Ricardo ; Hensman, James ; Zwießele, Max et al. / Hybrid discriminative-generative approach with Gaussian processes. In: Proceedings of Machine Learning Research. 2014 ; Vol. 33. pp. 47-56.

Bibtex

@article{1e3e00048c4247eaba0212b352451462,

title = "Hybrid discriminative-generative approach with Gaussian processes",

abstract = "Machine learning practitioners are often faced with a choice between a discriminative and a generative approach to modelling. Here, we present a model based on a hybrid approach that breaks down some of the barriers between the discriminative and generative points of view, allowing continuous dimensionality reduction of hybrid discrete-continuous data, discriminative classification with missing inputs and manifold learning informed by class labels.",

author = "Ricardo Andrade-Pacheco and James Hensman and Max Zwie{\ss}ele and Lawrence, {Neil D.}",

year = "2014",

language = "English",

volume = "33",

pages = "47--56",

journal = "Proceedings of Machine Learning Research",

issn = "1938-7228",

}

RIS

TY - JOUR

T1 - Hybrid discriminative-generative approach with Gaussian processes

AU - Andrade-Pacheco, Ricardo

AU - Hensman, James

AU - Zwießele, Max

AU - Lawrence, Neil D.

PY - 2014

Y1 - 2014

N2 - Machine learning practitioners are often faced with a choice between a discriminative and a generative approach to modelling. Here, we present a model based on a hybrid approach that breaks down some of the barriers between the discriminative and generative points of view, allowing continuous dimensionality reduction of hybrid discrete-continuous data, discriminative classification with missing inputs and manifold learning informed by class labels.

AB - Machine learning practitioners are often faced with a choice between a discriminative and a generative approach to modelling. Here, we present a model based on a hybrid approach that breaks down some of the barriers between the discriminative and generative points of view, allowing continuous dimensionality reduction of hybrid discrete-continuous data, discriminative classification with missing inputs and manifold learning informed by class labels.

M3 - Journal article

AN - SCOPUS:84955455292

VL - 33

SP - 47

EP - 56

JO - Proceedings of Machine Learning Research

JF - Proceedings of Machine Learning Research

SN - 1938-7228

ER -

Research

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