Hidden markov processes
An overview of statistical and information-theoretic aspects of hidden Markov processes
(HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain …
(HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain …
Markov chain Monte Carlo methods: computation and inference
S Chib - Handbook of econometrics, 2001 - Elsevier
This chapter reviews the recent developments in Markov chain Monte Carlo simulation
methods. These methods, which are concerned with the simulation of high dimensional …
methods. These methods, which are concerned with the simulation of high dimensional …
Quantifying location privacy
R Shokri, G Theodorakopoulos… - … IEEE symposium on …, 2011 - ieeexplore.ieee.org
It is a well-known fact that the progress of personal communication devices leads to serious
concerns about privacy in general, and location privacy in particular. As a response to these …
concerns about privacy in general, and location privacy in particular. As a response to these …
[图书][B] Markov chain Monte Carlo in practice
WR Gilks, S Richardson, D Spiegelhalter - 1995 - books.google.com
General state-space Markov chain theory has evolved to make it both more accessible and
more powerful. Markov Chain Monte Carlo in Practice introduces MCMC methods and their …
more powerful. Markov Chain Monte Carlo in Practice introduces MCMC methods and their …
Springer Series in Statistics
Hidden Markov models—most often abbreviated to the acronym “HMMs”—are one of the
most successful statistical modelling ideas that have came up in the last forty years: the use …
most successful statistical modelling ideas that have came up in the last forty years: the use …
[图书][B] Variational algorithms for approximate Bayesian inference
MJ Beal - 2003 - search.proquest.com
The Bayesian framework for machine learning allows for the incorporation of prior
knowledge in a coherent way, avoids overfitting problems, and provides a principled basis …
knowledge in a coherent way, avoids overfitting problems, and provides a principled basis …
[图书][B] Finite mixture and Markov switching models
S Frühwirth-Schnatter - 2006 - Springer
Modelling based on finite mixture distributions is a rapidly developing area with the range of
applications exploding. Finite mixture models are nowadays applied in such diverse areas …
applications exploding. Finite mixture models are nowadays applied in such diverse areas …
[PDF][PDF] Bayesian filtering: From Kalman filters to particle filters, and beyond
Z Chen - Statistics, 2003 - automatica.dei.unipd.it
In this self-contained survey/review paper, we systematically investigate the roots of
Bayesian filtering as well as its rich leaves in the literature. Stochastic filtering theory is …
Bayesian filtering as well as its rich leaves in the literature. Stochastic filtering theory is …
An introduction to hidden Markov models and Bayesian networks
Z Ghahramani - International journal of pattern recognition and …, 2001 - World Scientific
We provide a tutorial on learning and inference in hidden Markov models in the context of
the recent literature on Bayesian networks. This perspective makes it possible to consider …
the recent literature on Bayesian networks. This perspective makes it possible to consider …
Hidden Markov models and their applications in biological sequence analysis
BJ Yoon - Current genomics, 2009 - ingentaconnect.com
Hidden Markov models (HMMs) have been extensively used in biological sequence
analysis. In this paper, we give a tutorial review of HMMs and their applications in a variety …
analysis. In this paper, we give a tutorial review of HMMs and their applications in a variety …