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» Maximum likelihood analysis of algorithms and data structure...
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185
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ACIVS
2005
Springer
15 years 12 months ago
A Likelihood Ratio Test for Functional MRI Data Analysis to Account for Colored Noise
Abstract. Functional magnetic resonance (fMRI) data are often corrupted with colored noise. To account for this type of noise, many prewhitening and pre-coloring strategies have be...
Jan Sijbers, Arnold Jan den Dekker, Robert Bos
214
Voted
ICML
2005
IEEE
16 years 7 months ago
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
155
Voted
DAGM
2004
Springer
15 years 11 months ago
A Probabilistic Framework for Robust and Accurate Matching of Point Clouds
We present a probabilistic framework for matching of point clouds. Variants of the ICP algorithm typically pair points to points or points to lines. Instead, we pair data points to...
Peter Biber, Sven Fleck, Wolfgang Straßer
152
Voted
NECO
2000
88views more  NECO 2000»
15 years 6 months ago
Practical Identifiability of Finite Mixtures of Multivariate Bernoulli Distributions
The class of finite mixtures of multivariate Bernoulli distributions is known to be nonidentifiable, i.e., different values of the mixture parameters can correspond to exactly the...
Miguel Á. Carreira-Perpiñán, ...
161
Voted
ICML
2003
IEEE
16 years 7 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...