354 search results - page 11 / 71 » Estimating random variables from random sparse observations |
ICIP
2000
IEEE
2000
IEEE
Motion Estimation Using Adaptive Blocksize Observation Model and Efficient Multiscale Regularization
14 years 9 months ago
Bayesian motion estimation requires two pdf models: observation model and motion field (prior) model. The optimization process for this method uses sequential approach, e.g. simul...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
In this paper we propose novel algorithms for image restoration and parameter estimation with a Generalized Gaussian Markov Random Field prior utilizing variational distribution a...
INFORMATICALT
2000
13 years 7 months ago
2000
Abstract. Influence of projection pursuit on classification errors and estimates of a posteriori probabilities from the sample is considered. Observed random variable is supposed t...
ICMLA
2007
13 years 9 months ago
2007
For both single probability estimation trees (PETs) and ensembles of such trees, commonly employed class probability estimates correct the observed relative class frequencies in e...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sens...