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» Grid based variational approximations
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DSMML
2004
Springer
14 years 2 months ago
Variational Bayes Estimation of Mixing Coefficients
We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 a...
Bo Wang 0002, D. M. Titterington
NIPS
2007
14 years 9 days ago
Variational inference for Markov jump processes
Markov jump processes play an important role in a large number of application domains. However, realistic systems are analytically intractable and they have traditionally been ana...
Manfred Opper, Guido Sanguinetti
ICML
2004
IEEE
14 years 11 months ago
Variational methods for the Dirichlet process
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
David M. Blei, Michael I. Jordan
HPDC
2002
IEEE
14 years 3 months ago
Predicting Sporadic Grid Data Transfers
The increasingly common practice of replicating datasets and using resources as distributed data stores in Grid environments has led to the problem of determining which replica ca...
Sudharshan Vazhkudai, Jennifer M. Schopf
SIAMNUM
2010
105views more  SIAMNUM 2010»
13 years 5 months ago
Quantization Based Filtering Method Using First Order Approximation
The quantization based filtering method (see [13], [14]) is a grid based approximation method to solve nonlinear filtering problems with discrete time observations. It relies on o...
Afef Sellami