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Advanced Markov chain Monte Carlo methods: learning from past samples

2010

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An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization

Statistics and computing, 2022-08, Vol.32 (4), Article 58

2022

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Drug sensitivity prediction with high-dimensional mixture regression

PloS one, 2019-02, Vol.14 (2), p.e0212108-e0212108

2019

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Enhanced construction of gene regulatory networks using hub gene information

BMC bioinformatics, 2017-03, Vol.18 (1), p.186, Article 186

2017

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Improving SAMC Using Smoothing Methods: Theory and Applications to Bayesian Model Selection Problems

The Annals of statistics, 2009-10, Vol.37 (5B), p.2626-2654

Liang, Faming

2009

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Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests

1st, 2023

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Nearly optimal Bayesian shrinkage for high-dimensional regression

Science China. Mathematics, 2023-02, Vol.66 (2), p.409-442

2023

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Annealing stochastic approximation Monte Carlo algorithm for neural network training

Machine learning, 2007-10, Vol.68 (3), p.201-233

Liang, Faming

2007

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Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis

Journal of thoracic oncology, 2017-03, Vol.12 (3), p.501-509

2017

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TRAJECTORY AVERAGING FOR STOCHASTIC APPROXIMATION MCMC ALGORITHMS

The Annals of statistics, 2010-10, Vol.38 (5), p.2823-2856

Liang, Faming

2010

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Stochastic Approximation in Monte Carlo Computation

Journal of the American Statistical Association, 2007-03, Vol.102 (477), p.305-320

2007

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On the use of stochastic approximation Monte Carlo for Monte Carlo integration

Statistics & probability letters, 2009-03, Vol.79 (5), p.581-587

Liang, Faming

2009

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Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

Journal of hydrology (Amsterdam), 2011-11, Vol.409 (3), p.696-709

2011

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Bayesian detection of causal rare variants under posterior consistency

PloS one, 2013-07, Vol.8 (7), p.e69633-e69633

2013

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Estimating uncertainty of streamflow simulation using Bayesian neural networks

Water resources research, 2009-02, Vol.45 (2), p.W02403-n/a

2009

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Robust Clustering Using Exponential Power Mixtures

Biometrics, 2010-12, Vol.66 (4), p.1078-1086

2010

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Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data

Journal of the American Statistical Association, 2013-03, Vol.108 (501), p.325-339

2013

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Use of SVD-based probit transformation in clustering gene expression profiles

Computational statistics & data analysis, 2007-08, Vol.51 (12), p.6355-6366

Liang, Faming

2007

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Bayesian Peak Picking for NMR Spectra

Genomics, proteomics & bioinformatics, 2014-02, Vol.12 (1), p.39-47

2014

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Markov neighborhood regression for statistical inference of high‐dimensional generalized linear models

Statistics in medicine, 2022-09, Vol.41 (20), p.4057-4078

2022

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A kernel‐expanded stochastic neural network

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2022-04, Vol.84 (2), p.547-578

2022

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split‐and‐merge Bayesian variable selection approach for ultrahigh dimensional regression

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2015-11, Vol.77 (5), p.947-972

2015

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Bayesian modeling of ChIP-chip data using latent variables

BMC bioinformatics, 2009-10, Vol.10 (1), p.352-352, Article 352

2009

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A Generalized Wang-Landau Algorithm for Monte Carlo Computation

Journal of the American Statistical Association, 2005-12, Vol.100 (472), p.1311-1327

Liang, Faming

2005

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High-Dimensional Variable Selection With Reciprocal L1-Regularization

Journal of the American Statistical Association, 2015-10, Vol.110 (512), p.1607-1620

2015

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Advanced Markov chain Monte Carlo methods: learning from past samples

An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization

Drug sensitivity prediction with high-dimensional mixture regression

Enhanced construction of gene regulatory networks using hub gene information

Improving SAMC Using Smoothing Methods: Theory and Applications to Bayesian Model Selection Problems

Sparse Graphical Modeling for High Dimensional Data: A Paradigm of Conditional Independence Tests

Nearly optimal Bayesian shrinkage for high-dimensional regression

Annealing stochastic approximation Monte Carlo algorithm for neural network training

Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis

TRAJECTORY AVERAGING FOR STOCHASTIC APPROXIMATION MCMC ALGORITHMS

Stochastic Approximation in Monte Carlo Computation

On the use of stochastic approximation Monte Carlo for Monte Carlo integration

Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

Bayesian detection of causal rare variants under posterior consistency

Estimating uncertainty of streamflow simulation using Bayesian neural networks

Robust Clustering Using Exponential Power Mixtures

Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data

Use of SVD-based probit transformation in clustering gene expression profiles

Bayesian Peak Picking for NMR Spectra

Markov neighborhood regression for statistical inference of high‐dimensional generalized linear models

A kernel‐expanded stochastic neural network

split‐and‐merge Bayesian variable selection approach for ultrahigh dimensional regression

Bayesian modeling of ChIP-chip data using latent variables

A Generalized Wang-Landau Algorithm for Monte Carlo Computation

High-Dimensional Variable Selection With Reciprocal L1-Regularization

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