112 search results - page 20 / 23 » Gaussian Processes for Machine Learning (GPML) Toolbox |
136
Voted
ISM
2008
IEEE
15 years 10 months ago
2008
IEEE
Many multimedia applications rely on the computation of logarithms, for example, when estimating log-likelihoods for Gaussian Mixture Models. Knowing of the demand to compute loga...
114
Voted
ICWSM
2009
15 years 1 months ago
2009
In this paper we present a regression-based machine learning approach to email thread summarization. The regression model is able to take advantage of multiple gold-standard annot...
130
Voted
ICML
2006
IEEE
16 years 4 months ago
2006
IEEE
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
147
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ACML
2009
Springer
15 years 10 months ago
2009
Springer
Many regression schemes deliver a point estimate only, but often it is useful or even essential to quantify the uncertainty inherent in a prediction. If a conditional density estim...
148
Voted
ECML
2006
Springer
15 years 7 months ago
2006
Springer
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...