Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo

DOI10.1080/10618600.2023.2170089arXiv2201.00092OpenAlexW4319836241MaRDI QIDQ6180725

Eric C. Chi, Unnamed Author, Hua Zhou

Publication date: 22 January 2024

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2201.00092

zbMATH Keywords

convex optimizationHamiltonian Monte Carloepigraphstrend filteringMoreau-Yosida envelope

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Nearly unbiased variable selection under minimax concave penalty
• Nonlinear total variation based noise removal algorithms
• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
• Fixed-point algorithms for inverse problems in science and engineering. Based on the presentations at the interdisciplinary workshop, BIRS, Banff, Canada, November 1--6, 2009.
• Splines in higher order TV regularization
• Exponential convergence of Langevin distributions and their discrete approximations
• An algorithm for total variation minimization and applications
• Locally adaptive smoothing with Markov random fields and shrinkage priors
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Adaptive piecewise polynomial estimation via trend filtering
• Proximal Markov chain Monte Carlo algorithms
• Bayesian Spectral Analysis Regression with Shape Restrictions
• Bayesian estimation and inference for generalised partial linear models using shape-restricted splines
• The Split Bregman Method for L1-Regularized Problems
• Accelerating Proximal Markov Chain Monte Carlo by Using an Explicit Stabilized Method
• Bayesian Isotonic Regression and Trend Analysis
• The horseshoe estimator for sparse signals
• $\ell_1$ Trend Filtering
• The Bayesian Lasso
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• First-Order Methods in Optimization
• Sparsity and Smoothness Via the Fused Lasso
• Gaussian Markov Random Fields
• Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau
• Multivariate output analysis for Markov chain Monte Carlo
• A Proximal Markov Chain Monte Carlo Method for Bayesian Inference in Imaging Inverse Problems: When Langevin Meets Moreau
• A variable selection approach to monotonic regression with Bernstein polynomials
• Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach Part I: Methodology and Experiments
• Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis
• Dynamic Shrinkage Processes
• The Support Reduction Algorithm for Computing Non‐Parametric Function Estimates in Mixture Models

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