49 search results - page 9 / 10 » Semi-Supervised Learning via Generalized Maximum Entropy |
CVPR
2007
IEEE
14 years 7 months ago
2007
IEEE
This paper presents robust click-point linking: a novel localized registration framework that allows users to interactively prescribe where the accuracy has to be high. By emphasi...
CORR
2011
Springer
13 years 11 days ago
2011
Springer
Modeling the behavior of imperfect agents from a small number of observations is a difficult, but important task. In the singleagent decision-theoretic setting, inverse optimal co...
BMEI
2009
IEEE
13 years 6 months ago
2009
IEEE
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
NIPS
1998
13 years 6 months ago
1998
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
IJON
1998
13 years 5 months ago
1998
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...