48 search results - page 4 / 10 » Learning from measurements in exponential families |
ICDM
2007
IEEE
14 years 1 months ago
2007
IEEE
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
We introduce an expectation maximizationtype (EM) algorithm for maximum likelihood optimization of conditional densities. It is applicable to hidden variable models where the dist...
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
EUROCOLT
1999
Springer
13 years 11 months ago
1999
Springer
Abstract. Recent works have shown the advantage of using Active Learning methods, such as the Query by Committee (QBC) algorithm, to various learning problems. This class of Algori...
NIPS
2007
13 years 8 months ago
2007
Many perceptual processes and neural computations, such as speech recognition, motor control and learning, depend on the ability to measure and mark the passage of time. However, ...