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TNN
1998
89views more  TNN 1998»
13 years 8 months ago
Fast training of recurrent networks based on the EM algorithm
— In this work, a probabilistic model is established for recurrent networks. The EM (expectation-maximization) algorithm is then applied to derive a new fast training algorithm f...
Sheng Ma, Chuanyi Ji
COLING
2002
13 years 8 months ago
Base Noun Phrase Translation Using Web Data and the EM Algorithm
We consider here the problem of Base Noun Phrase translation. We propose a new method to perform the task. For a given Base NP, we first search its translation candidates from the...
Yunbo Cao, Hang Li
CSDA
2007
81views more  CSDA 2007»
13 years 8 months ago
A stochastic EM algorithm for a semiparametric mixture model
Recently, there has been a considerable interest in finite mixture models with semi-/non-parametric component distributions. Identifiability of such model parameters is generall...
Laurent Bordes, Didier Chauveau, Pierre Vandekerkh...
CSDA
2007
108views more  CSDA 2007»
13 years 8 months ago
Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm
Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/ pharmacodynamic (PK/PD) phenotypes. An EM algorithm for maxim...
Xiaoning Wang, Alan Schumitzky, David Z. D'Argenio
ICML
2008
IEEE
14 years 9 months ago
Fully distributed EM for very large datasets
In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of th...
Jason Wolfe, Aria Haghighi, Dan Klein