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