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Consistent Distribution Regression via Mean Embedding

Szabo, Z; Gretton, A; Póczos, B; Sriperumbudur, B; (2014) Consistent Distribution Regression via Mean Embedding. Presented at: University of Hertfordshire, Computer Science Research Colloquium, Hatfield, UK. Green open access

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Abstract

In a standard regression model we need to predict a real-valued response based on a vector input. Recently, there has been a significant interest in extending the prediction problem from finite-dimensional Euclidean input spaces to other domains such as distributions. In my talk I am going to present a general, consistent and at the same time computationally very simple approach to solve the corresponding distribution regression task for the case when we have only samples from the distributions using mean embeddings. I also demonstrate the efficiency of our method on (i) entropy and skewness estimation of distributions, and (ii) on aerosol prediction based on satellite images.

Type: Conference item (Presentation)
Title: Consistent Distribution Regression via Mean Embedding
Event: University of Hertfordshire, Computer Science Research Colloquium
Location: Hatfield, UK
Dates: 2014-03-05 - 2014-03-05
Open access status: An open access version is available from UCL Discovery
Publisher version: http://cs-colloq.stca.herts.ac.uk/
Language: English
Additional information: http://arxiv.org/abs/1402.1754
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit
URI: https://discovery.ucl.ac.uk/id/eprint/1433100
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