Efficient Bayesian estimation and use of cut posterior in semiparametric
hidden Markov models

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Efficient Bayesian estimation and use of cut posterior in semiparametric hidden Markov models

11 March 2022

Daniella F Moss

Judith Rousseau

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Papers citing "Efficient Bayesian estimation and use of cut posterior in semiparametric hidden Markov models"

19 / 19 papers shown

Title
Fundamental limits for learning hidden Markov model parameters Kweku Abraham Zacharie Naulet Elisabeth Gassiat 59 6 0 24 Jun 2021
Stochastic Approximation Cut Algorithm for Inference in Modularized Bayesian Models Yang Liu Robert J. B. Goudie 29 18 0 02 Jun 2020
Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components Chris U. Carmona Geoff K. Nicholls 114 27 0 15 Mar 2020
Efficient semiparametric estimation and model selection for multidimensional mixtures Elisabeth Gassiat Judith Rousseau E. Vernet 81 10 0 19 Jul 2016
Non Parametric Hidden Markov Models with Finite State Space: Posterior Concentration Rates E. Vernet 333 9 0 27 Nov 2015
Consistent estimation of the filtering and marginal smoothing distributions in nonparametric hidden Markov models Yohann De Castro Elisabeth Gassiat Sylvain Le Corff 47 32 0 23 Jul 2015
Minimax adaptive estimation of nonparametric hidden Markov models Yohann De Castro Elisabeth Gassiat C. Lacour 59 32 0 20 Jan 2015
Nonparametric identification and maximum likelihood estimation for hidden Markov model Grigory Alexandrovich H. Holzmann Anna Leister 83 33 0 16 Apr 2014
Posterior consistency for nonparametric hidden Markov models with finite state space E. Vernet 74 24 0 13 Nov 2013
A Bernstein-von Mises theorem for smooth functionals in semiparametric models I. Castillo Judith Rousseau 140 117 0 20 May 2013
Tensor decompositions for learning latent variable models Anima Anandkumar Rong Ge Daniel J. Hsu Sham Kakade Matus Telgarsky 450 1,149 0 29 Oct 2012
About the posterior distribution in hidden Markov models with unknown number of states Elisabeth Gassiat Judith Rousseau 76 34 0 09 Jul 2012
Learning mixtures of spherical Gaussians: moment methods and spectral decompositions Daniel J. Hsu Sham Kakade 237 327 0 25 Jun 2012
A Spectral Algorithm for Latent Dirichlet Allocation Anima Anandkumar Dean Phillips Foster Daniel J. Hsu Sham Kakade Yi-Kai Liu 192 301 0 30 Apr 2012
A Method of Moments for Mixture Models and Hidden Markov Models Anima Anandkumar Daniel J. Hsu Sham Kakade 201 344 0 03 Mar 2012
Bernstein Von Mises Theorem for linear functionals of the density Vincent Rivoirard Judith Rousseau 144 122 0 28 Aug 2009
A Spectral Algorithm for Learning Hidden Markov Models Daniel J. Hsu Sham Kakade Tong Zhang 201 310 0 26 Nov 2008
Identifiability of parameters in latent structure models with many observed variables E. Allman C. Matias J. Rhodes CML 159 534 0 29 Sep 2008
Convergence rates of posterior distributions for noniid observations S. Ghosal A. van der Vaart 404 399 0 03 Aug 2007