Fetching the paper…
Reading the bibliography…
Sampling from various kinds of distributions is an issue of paramount importance in statistics since it is often the key ingredient for constructing estimators, test procedures or confidence intervals.
A bridge between nonlinear time series models and nonlinear stochastic dynamical systems: a local linearization approach
T. Ozaki · 1992
Earlier work this paper cites.
Sampling from log-concave distributions
A. Frieze, R. Kannan, and N. Polson · 1994
Earlier work this paper cites.
Computable bounds for geometric convergence rates of Markov chains
S. P. Meyn and R. L. Tweedie · 1994
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.
Estimation of spectral gap for elliptic operators
Mu-Fa Chen and Feng-Yu Wang · 1997
Earlier work this paper cites.
MCMC convergence diagnosis via multivariate bounds on log-concave densities
S. P. Brooks · 1998
Earlier work this paper cites.
Optimal scaling of discrete approximations to Langevin diffusions
G. O. Roberts and J. S. Rosenthal · 1998
Earlier work this paper cites.
Log-Sobolev inequalities and sampling from log-concave distributions
A. Frieze and R. Kannan · 1999
Earlier work this paper cites.
Geometric ergodicity of Metropolis algorithms
S. F. Jarner and E. Hansen · 2000
Earlier work this paper cites.
Recursive computation of the invariant distribution of a diffusion
D. Lamberton and G. Pagès · 2002
Earlier work this paper cites.
Langevin diffusions and Metropolis-Hastings algorithms
G. O. Roberts and O. Stramer · 2002
Earlier work this paper cites.
Quantitative convergence rates of Markov chains: a simple account
J. S. Rosenthal · 2002
Earlier work this paper cites.
Convex optimization
S. Boyd and L. Vandenberghe · 2004
Cited alongside, same era.
Quantitative bounds on convergence of time-inhomogeneous Markov chains
R. Douc, E. Moulines, and Jeffrey S. Rosenthal · 2004
Cited alongside, same era.
Introductory lectures on convex optimization , volume 87 of Applied Optimization
Yu. Nesterov · 2004
Cited alongside, same era.
General state space markov chains and mcmc algorithms
G. O. Roberts and J. S. Rosenthal · 2004
Cited alongside, same era.
Estimation numérique de la mesure invariante d’un processus de diffusion
V. Lemaire · 2005
Cited alongside, same era.
Bayesian auxiliary variable models for binary and multinomial regression
C. Holmes and L. Held · 2006
Cited alongside, same era.
Sparse regression learning by aggregation and Langevin Monte-Carlo
A. S. Dalalyan and A. B. Tsybakov · 2012
Later among the works it cites.
Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions
N. S. Pillai, A. M. Stuart, and A. H. Thiéry · 2012
Later among the works it cites.
Convergence rates for MCMC algorithms for a robust Bayesian binary regression model
V. Roy · 2012
Later among the works it cites.
Nonasymptotic mixing of the MALA algorithm
N. Bou-Rabee and M. Hairer · 2013
Later among the works it cites.
A shrinkage-thresholding metropolis adjusted langevin algorithm for bayesian variable selection
A. Schreck, G. Fort, S. Le Corff, and E. Moulines · 2013
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Fast algorithms for logconcave functions: Sampling, rounding, integration and optimization
L. Lovász and S. Vempala · 2006
Cited alongside, same era.
On the computational complexity of MCMC-based estimators in large samples
A. Belloni and V. Chernozhukov · 2009
Cited alongside, same era.
Sparse regression learning by aggregation and langevin monte-carlo
A. S. Dalalyan and A. B. Tsybakov · 2009
Cited alongside, same era.
Adaptive Markov chain Monte Carlo: theory and methods
Y. Atchadé, G. Fort, E. Moulines, and P. Priouret · 2011
Cited alongside, same era.
Riemann manifold Langevin and Hamiltonian Monte Carlo methods
M. Girolami and B. Calderhead · 2011
Cited alongside, same era.
Hit-and-run from a corner
L. Lovász and S. Vempala
Cited in the paper.
D. Bakry, I. Gentil, and M. Ledoux · 2014
Closest in time.
Informative g g -priors for logistic regression
T. Hanson, A. Branscum, and W. Johnson · 2014
Closest in time.
Proximal markov chain monte carlo algorithms
M. Pereyra · 2014
Closest in time.
Log-concavity and strong log-concavity: a review
A. Saumard and J. A. Wellner · 2014
Closest in time.
Langevin diffusions and the Metropolis-adjusted Langevin algorithm
T. Xifara, C. Sherlock, S. Livingstone, S. Byrne, and M. Girolami · 2014
Closest in time.
Non-asymptotic convergence analysis for the unadjusted langevin algorithm
A. Durmus and E. Moulines · 2015
Closest in time.