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We study the problem of sampling from the power posterior distribution in Bayesian Gaussian mixture models, a robust version of the classical posterior.
A lower bound for the smallest eigenvalue of the Laplacian
J. Cheeger · 1969
Earlier work this paper cites.
A note on the isoperimetric constant
P. Buser · 1982
Earlier work this paper cites.
Probability in Banach Spaces: Isoperimetry and Processes
M. Ledoux and M. Talagrand · 1991
Earlier work this paper cites.
Random walks in a convex body and an improved volume algorithm
L. Lovász and M. Simonovits · 1993
Earlier work this paper cites.
A simple analytic proof of an inequality by P. Buser
M. Ledoux · 1994
Earlier work this paper cites.
The Fokker-Planck Equation
H. Risken · 1996
Earlier work this paper cites.
Exponential convergence of Langevin distributions and their discrete approximations
G. O. Roberts and R. L. Tweedie · 1996
Earlier work this paper cites.
Weak Convergence and Empirical Processes
A. W. van der Vaart and J. Wellner · 1996
Earlier work this paper cites.
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S. Tavaré, D. J. Balding, R. C. Griffiths, and P. I. Donnelly · 1997
Earlier work this paper cites.
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S. N. MacEachern and P. Müller · 1998
Earlier work this paper cites.
Isoperimetric and analytic inequalities for log-concave probability measures
S. G. Bobkov · 1999
Earlier work this paper cites.
Posterior consistency of Dirichlet mixtures in density estimation
S. Ghosal, J. K. Ghosh, and R. V. Ramamoorthi · 1999
Earlier work this paper cites.
Computational and inferential difficulties with mixture posterior distributions
G. Celeux, M. Hurn, and C. P. Robert · 2000
Earlier work this paper cites.
Markov chain sampling methods for Dirichlet process mixture models
R. M. Neal · 2000
Earlier work this paper cites.
Bayesian analysis of mixture models with an unknown number of components - an alternative to reversible jump methods
M. Stephens · 2000
Earlier work this paper cites.
Entropies and rates of convergence for maximum likelihood and Bayes estimation for mixtures of normal densities
S. Ghosal and A. van der Vaart · 2001
Earlier work this paper cites.
Hidden Markov models and desease mapping
P. Green and S. Richardson · 2001
Earlier work this paper cites.
Bayesian model selection in finite mixtures by marginal density decompositions
H. Ishwaran, L. F. James, and J. Sun · 2001
Earlier work this paper cites.
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M. A. Beaumont, W. Zhang, and D. J. Balding · 2002
Earlier work this paper cites.
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Theoretical guarantees for approximate sampling from smooth and log-concave densities
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Non-convex learning via stochastic gradient Langevin dynamics: A nonasymptotic analysis
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N. Bou-Rabee, A. Eberle, and R. Zimmer · 2018
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Posterior convergence rates of Dirichlet mixtures at smooth densities
S. Ghosal and A. van der Vaart · 2007
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A new criterion for the logarithmic Sobolev inequality and two applications
F. Otto and M. G. Reznikoff · 2007
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The nested Dirichlet process
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On the computational complexity of MCMC-based estimators in large samples
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Underdamped Langevin MCMC: A non-asymptotic analysis
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Beyond log-concavity: Provable guarantees for sampling multi-modal distributions using simulated tempering Langevin Monte Carlo
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Algorithmic theory of ODEs and sampling from well-conditioned logconcave densities
Y. T. Lee, Z. Song, and S. Vempala · 2018
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Dimensionally tight running time bounds for second-order Hamiltonian Monte Carlo
O. Mangoubi and N. K. Vishnoi · 2018
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Mixture models with a prior on the number of components
J. W. Miller and M. T. Harrison · 2018
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Bayesian fractional posteriors
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Sampling can be faster than optimization
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Robust Bayesian inference via coarsening
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High-dimensional statistics: A non-asymptotic viewpoint
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