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» Distributions of Maximum Likelihood Estimators and Model Com...
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NIPS
1998
14 years 11 months ago
Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm
We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...
Tony Jebara, Alex Pentland
ESCIENCE
2007
IEEE
15 years 4 months ago
Distributed and Generic Maximum Likelihood Evaluation
This paper presents GMLE 1 , a generic and distributed framework for maximum likelihood evaluation. GMLE is currently being applied to astroinformatics for determining the shape o...
Travis J. Desell, Nathan Cole, Malik Magdon-Ismail...
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NIPS
2007
14 years 11 months ago
Convex Clustering with Exemplar-Based Models
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Danial Lashkari, Polina Golland
CSDA
2007
101views more  CSDA 2007»
14 years 9 months ago
The evaluation of evidence for exponentially distributed data
At present, likelihood ratios for two-level models are determined with the use of a normal kernel estimation procedure when the between-group distribution is thought to be non-nor...
C. G. G. Aitken, Qiang Shen, Richard Jensen, B. Ha...
ICASSP
2008
IEEE
15 years 4 months ago
Weighted maximum likelihood autoregressive and moving average spectrum modeling
We propose new algorithms for estimating autoregressive (AR), moving average (MA), and ARMA models in the spectral domain. These algorithms are derived from a maximum likelihood a...
Roland Badeau, Bertrand David