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» Theory and Use of the EM Algorithm
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CSDA
2007
137views more  CSDA 2007»
15 years 1 months ago
Fitting finite mixtures of generalized linear regressions in R
R package flexmix provides flexible modelling of finite mixtures of regression models using the EM algorithm. Several new features of the software such as fixed and nested var...
Bettina Grün, Friedrich Leisch
VMCAI
2007
Springer
15 years 7 months ago
Invariant Synthesis for Combined Theories
We present a constraint-based algorithm for the synthesis of invariants expressed in the combined theory of linear arithmetic and uninterpreted function symbols. Given a set of pro...
Dirk Beyer, Thomas A. Henzinger, Rupak Majumdar, A...
SIGIR
2004
ACM
15 years 7 months ago
GaP: a factor model for discrete data
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
John F. Canny
SETN
2004
Springer
15 years 6 months ago
Incremental Mixture Learning for Clustering Discrete Data
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Konstantinos Blekas, Aristidis Likas
VG
2003
15 years 2 months ago
Rapid Emission Tomography Reconstruction
We present new implementations of the Maximum Likelihood Expectation Maximization (EM) algorithm and the related Ordered Subset EM (OSEM) algorithm. Our implementation is based on...
Ken Chidlow, Torsten Möller