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Hybrid discriminative-generative approach with Gaussian processes

Research output: Contribution to journalJournal article

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  • Ricardo Andrade-Pacheco
  • James Hensman
  • Max Zwießele
  • Neil D. Lawrence
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<mark>Journal publication date</mark>2014
<mark>Journal</mark>Proceedings of Machine Learning Research
Volume33
Number of pages10
Pages (from-to)47-56
<mark>State</mark>Published
<mark>Original language</mark>English

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.