A tutorial on MM algorithms
Most problems in frequentist statistics involve optimization of a function such as a likelihood
or a sum of squares. EM algorithms are among the most effective algorithms for maximum …
or a sum of squares. EM algorithms are among the most effective algorithms for maximum …
Surrogate maximization/minimization algorithms for adaboost and the logistic regression model
Surrogate maximization (or minimization)(SM) algorithms are a family of algorithm that can
be regarded as a generalization of expectation-maximization (EM) algorithms. There are …
be regarded as a generalization of expectation-maximization (EM) algorithms. There are …
[图书][B] Multi-rate modeling, model inference, and estimation for statistical classifiers
O Cetin - 2004 - search.proquest.com
Pattern classification problems arise in a wide variety of applications ranging from speech
recognition to machine tool-wear condition monitoring. In the statistical approach to pattern …
recognition to machine tool-wear condition monitoring. In the statistical approach to pattern …
[图书][B] Adaptive classifier design using labelled and unlabelled data
B Krishnapuram - 2004 - search.proquest.com
In statistical pattern recognition the goal is to accurately classify samples based on a set of
descriptive predictor variables (features). The design of pattern recognition systems involves …
descriptive predictor variables (features). The design of pattern recognition systems involves …
[引用][C] Mixture distributions (update)
DM Titterington - Encyclopedia of statistical sciences, 2004 - Wiley Online Library
[引用][C] Mixture Distributions—II
DM Titterington - Encyclopedia of Statistical Sciences, 2004 - Wiley Online Library