93 search results - page 3 / 19 » Learning Measurement Models for Unobserved Variables |
SASO
2009
IEEE
15 years 4 months ago
2009
IEEE
An optimal sensor layout is attained when a limited number of sensors are placed in an area such that the cost of the placement is minimised while the value of the obtained inform...
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
114
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ESOP
2011
Springer
14 years 29 days ago
2011
Springer
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
105
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AROBOTS
2011
14 years 4 months ago
2011
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
JMLR
2012
12 years 12 months ago
2012
We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...