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NIPS
2007
13 years 6 months ago
Expectation Maximization and Posterior Constraints
The expectation maximization (EM) algorithm is a widely used maximum likelihood estimation procedure for statistical models when the values of some of the variables in the model a...
João Graça, Kuzman Ganchev, Ben Task...
PKDD
2005
Springer
96views Data Mining» more  PKDD 2005»
13 years 10 months ago
Testing Theories in Particle Physics Using Maximum Likelihood and Adaptive Bin Allocation
We describe a methodology to assist scientists in quantifying the degree of evidence in favor of a new proposed theory compared to a standard baseline theory. The figure of merit ...
Bruce Knuteson, Ricardo Vilalta
ICML
2003
IEEE
14 years 6 months ago
Optimization with EM and Expectation-Conjugate-Gradient
We show a close relationship between the Expectation - Maximization (EM) algorithm and direct optimization algorithms such as gradientbased methods for parameter learning. We iden...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
ICASSP
2008
IEEE
13 years 11 months ago
Maximum likelihood approach to speech enhancement for noisy reverberant signals
This paper proposes a speech enhancement method for signals contaminated by room reverberation and additive background noise. The following conditions are assumed: (1) The spectra...
Takuya Yoshioka, Tomohiro Nakatani, Takafumi Hikic...
PR
2002
108views more  PR 2002»
13 years 4 months ago
Hyperparameter estimation for satellite image restoration using a MCMC maximum-likelihood method
The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ' function, involving two hyper...
André Jalobeanu, Laure Blanc-Féraud,...