All Stories

  1. A Robust Model-Free Feature Screening Method for Ultrahigh-Dimensional Data

    Article • Journal of Computational and Graphical Statistics, October 2017, Taylor & Francis

    Professor Faming Liang

  2. High-Dimensional Variable Selection With Reciprocal L1-Regularization

    Article • Journal of the American Statistical Association, October 2015, Taylor & Francis

    Professor Faming Liang

  3. A split-and-merge Bayesian variable selection approach for ultrahigh dimensional regression

    Article • Journal of the Royal Statistical Society Series B (Statistical Methodology), December 2014, Wiley

    Professor Faming Liang

  4. Weak Convergence Rates of Population Versus Single-Chain Stochastic Approximation MCMC Algorithms

    Article • Advances in Applied Probability, December 2014, Cambridge University Press

    Professor Faming Liang

  5. An Overview of Stochastic Approximation Monte Carlo

    Article • Wiley Interdisciplinary Reviews Computational Statistics, June 2014, Wiley

    Professor Faming Liang

  6. Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule

    Article • Journal of the American Statistical Association, April 2014, Taylor & Francis

    Professor Faming Liang

  7. Use of SAMC for Bayesian analysis of statistical models with intractable normalizing constants

    Article • Computational Statistics & Data Analysis, March 2014, Elsevier

    Professor Faming Liang

  8. Bayesian site selection for fast Gaussian process regression

    Article • IIE Transactions, February 2014, Taylor & Francis

    Professor Faming Liang

  9. Bayesian Peak Picking for NMR Spectra

    Article • Genomics Proteomics & Bioinformatics, February 2014, Oxford University Press (OUP)

    Professor Faming Liang

  10. A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

    Article • Statistica Sinica, January 2014, Institute of Statistical Science

    Professor Faming Liang

  11. Model-Free Inference for ChIP-Seq Data

    Article • Journal of Data Mining in Genomics & Proteomics, January 2014, OMICS Publishing Group

    Professor Faming Liang

  12. Fitting Social Network Models Using Varying Truncation Stochastic Approximation MCMC Algorithm

    Article • Journal of Computational and Graphical Statistics, October 2013, Taylor & Francis

    Professor Faming Liang

  13. A fast multilocus test with adaptive SNP selection for large-scale genetic-association studies

    Article • European Journal of Human Genetics, September 2013, Springer Science + Business Media

    Professor Faming Liang

  14. Statistical Properties of Horizontally Oriented Plates in Optically Thick Clouds From Satellite Observations

    Article • IEEE Geoscience and Remote Sensing Letters, September 2013, Institute of Electrical & Electronics Engineers (IEEE)

    Professor Faming Liang

  15. A Monte Carlo Metropolis-Hastings Algorithm for Sampling from Distributions with Intractable Normalizing Constants

    Article • Neural Computation, August 2013, The MIT Press

    Professor Faming Liang

  16. Bayesian Detection of Causal Rare Variants under Posterior Consistency

    Article • PLoS ONE, July 2013, PLOS

    Professor Faming Liang

  17. Bayesian Subset Modeling for High-Dimensional Generalized Linear Models

    Article • Journal of the American Statistical Association, June 2013, Taylor & Francis

    Professor Faming Liang

  18. Sea Surface Temperature Modeling using Radial Basis Function Networks With a Dynamically Weighted Particle Filter

    Article • Journal of the American Statistical Association, March 2013, Taylor & Francis

    Professor Faming Liang

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

    Article • Journal of the American Statistical Association, March 2013, Taylor & Francis

    Professor Faming Liang

  20. Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities

    Article • Statistics and Computing, February 2013, Springer Science + Business Media

    Professor Faming Liang

  21. Population SAMC vs SAMC: Convergence and Applications to Gene Selection Problems

    Article • Journal of Biometrics & Biostatistics, January 2013, OMICS Publishing Group

    Professor Faming Liang

  22. Bayesian analysis for exponential random graph models using the adaptive exchange sampler

    Article • Statistics and Its Interface, January 2013, International Press of Boston

    Professor Faming Liang

  23. Bayesian Analysis of Geostatistical Models With an Auxiliary Lattice

    Article • Journal of Computational and Graphical Statistics, April 2012, Taylor & Francis

    Professor Faming Liang

  24. Intrinsic Regression Models for Medial Representation of Subcortical Structures

    Article • Journal of the American Statistical Association, March 2012, Taylor & Francis

    Professor Faming Liang, Dr Martin A Styner

  25. A Flexible Bayesian Model for Studying Gene–Environment Interaction

    Article • PLoS Genetics, January 2012, PLOS

    Professor Faming Liang

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

    Article • Journal of Hydrology, November 2011, Elsevier

    Professor Faming Liang

  27. Folding small proteins via annealing stochastic approximation Monte Carlo

    Article • Biosystems, September 2011, Elsevier

    Professor Faming Liang

  28. BCL-2 (-938C > A) polymorphism is associated with breast cancer susceptibility

    Article • BMC Medical Genetics, April 2011, Springer Science + Business Media

    Professor Faming Liang

  29. Stochastic Generalized Method of Moments

    Article • Journal of Computational and Graphical Statistics, January 2011, Taylor & Francis

    Professor Faming Liang

  30. Robust Clustering Using Exponential Power Mixtures

    Article • Biometrics, December 2010, Oxford University Press (OUP)

    Professor Faming Liang

  31. Bayesian Modeling of ChIP‐chip Data Through a High‐Order Ising Model

    Article • Biometrics, December 2010, Oxford University Press (OUP)

    Professor Faming Liang

  32. Trajectory averaging for stochastic approximation MCMC algorithms

    Article • The Annals of Statistics, October 2010, Institute of Mathematical Statistics

    Professor Faming Liang

  33. A double Metropolis–Hastings sampler for spatial models with intractable normalizing constants

    Article • Journal of Statistical Computation and Simulation, September 2010, Taylor & Francis

    Professor Faming Liang

  34. Advanced Markov Chain Monte Carlo Methods

    Article • July 2010, Wiley

    Professor Faming Liang

  35. Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo

    Article • Canadian Journal of Statistics, May 2010, Wiley

    Professor Faming Liang

  36. Annealing evolutionary stochastic approximation Monte Carlo for global optimization

    Article • Statistics and Computing, April 2010, Springer Science + Business Media

    Professor Faming Liang

  37. Modeling the Relationship Between EDI Implementation and Firm Performance Improvement With Neural Networks

    Article • IEEE Transactions on Automation Science and Engineering, January 2010, Institute of Electrical & Electronics Engineers (IEEE)

    Professor Faming Liang

  38. Monte Carlo dynamically weighted importance sampling for spatial models with intractable normalizing constants

    Article • Journal of Physics Conference Series, December 2009, Institute of Physics Publishing

    Professor Faming Liang

  39. Bayesian phylogeny analysis via stochastic approximation Monte Carlo

    Article • Molecular Phylogenetics and Evolution, November 2009, Elsevier

    Professor Faming Liang

  40. Bayesian modeling of ChIP-chip data using latent variables

    Article • BMC Bioinformatics, October 2009, Springer Science + Business Media

    Professor Faming Liang

  41. Improving SAMC using smoothing methods: Theory and applications to Bayesian model selection problems

    Article • The Annals of Statistics, October 2009, Institute of Mathematical Statistics

    Professor Faming Liang

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

    Article • Statistics & Probability Letters, March 2009, Elsevier

    Professor Faming Liang

  43. Learning Bayesian networks for discrete data

    Article • Computational Statistics & Data Analysis, February 2009, Elsevier

    Professor Faming Liang

  44. Estimating uncertainty of streamflow simulation using Bayesian neural networks

    Article • Water Resources Research, February 2009, American Geophysical Union (AGU)

    Professor Faming Liang

  45. Bayesian Analysis of High Dimensional Classification

    Article • January 2009, American Institute of Physics

    Professor Faming Liang

  46. Crash Injury Severity Analysis Using Bayesian Ordered Probit Models

    Article • Journal of Transportation Engineering, January 2009, American Society of Civil Engineers (ASCE)

    Professor Faming Liang

  47. Annealing Stochastic Approximation Monte Carlo for Global Optimization

    Article • September 2008, IntechOpen

    Professor Faming Liang

  48. Convergence of stochastic approximation algorithms under irregular conditions

    Article • Statistica Neerlandica, July 2008, Wiley

    Professor Faming Liang

  49. Adaptive evolutionary Monte Carlo algorithm for optimization with applications to sensor placement problems

    Article • Statistics and Computing, July 2008, Springer Science + Business Media

    Professor Faming Liang

  50. Phylogenetic tree construction using sequential stochastic approximation Monte Carlo

    Article • Biosystems, January 2008, Elsevier

    Professor Faming Liang

  51. Inflammatory Gene Haplotype-Interaction Networks Involved in Coronary Collateral Formation

    Article • Human Heredity, January 2008, Karger Publishers

    Professor Faming Liang

  52. Continuous Contour Monte Carlo for Marginal Density Estimation With an Application to a Spatial Statistical Model

    Article • Journal of Computational and Graphical Statistics, September 2007, Taylor & Francis

    Professor Faming Liang

  53. Annealing stochastic approximation Monte Carlo algorithm for neural network training

    Article • Machine Learning, August 2007, Springer Science + Business Media

    Professor Faming Liang

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

    Article • Computational Statistics & Data Analysis, August 2007, Elsevier

    Professor Faming Liang

  55. Dynamic agglomerative clustering of gene expression profiles

    Article • Pattern Recognition Letters, July 2007, Elsevier

    Professor Faming Liang

  56. Stochastic Approximation in Monte Carlo Computation

    Article • Journal of the American Statistical Association, March 2007, Taylor & Francis

    Professor Faming Liang

  57. Stochastic Approximation Algorithms for Estimation of Spatial Mixed Models

    Article • January 2007, Elsevier

    Professor Faming Liang

  58. 18 Stochastic Approximation Algorithms for Estimation of Spatial Mixed Models

    Article • January 2007, Elsevier

    Professor Faming Liang

  59. Statistical and Computational Inverse Problems

    Article • Technometrics, February 2006, Taylor & Francis

    Professor Faming Liang

  60. A Theory on Flat Histogram Monte Carlo Algorithms

    Article • Journal of Statistical Physics, January 2006, Springer Science + Business Media

    Professor Faming Liang

  61. A Generalized Wang–Landau Algorithm for Monte Carlo Computation

    Article • Journal of the American Statistical Association, December 2005, Taylor & Francis

    Professor Faming Liang

  62. Determination of normalizing constants for simulated tempering

    Article • Physica A Statistical Mechanics and its Applications, October 2005, Elsevier

    Professor Faming Liang

  63. Evidence Evaluation for Bayesian Neural Networks Using Contour Monte Carlo

    Article • Neural Computation, June 2005, The MIT Press

    Professor Faming Liang

  64. Efficient MCMC estimation of discrete distributions

    Article • Computational Statistics & Data Analysis, June 2005, Elsevier

    Professor Faming Liang

  65. Bayesian neural networks for nonlinear time series forecasting

    Article • Statistics and Computing, January 2005, Springer Science + Business Media

    Professor Faming Liang

  66. Generalized1∕k-ensemble algorithm

    Article • Physical Review E, June 2004, American Physical Society (APS)

    Professor Faming Liang

  67. Annealing contour Monte Carlo algorithm for structure optimization in an off-lattice protein model

    Article • The Journal of Chemical Physics, March 2004, American Institute of Physics

    Professor Faming Liang

  68. Search for Haplotype Interactions That Influence Susceptibility to Type 1 Diabetes, through Use of Unphased Genotype Data

    Article • The American Journal of Human Genetics, December 2003, Elsevier

    Professor Faming Liang

  69. An Effective Bayesian Neural Network Classifier with a Comparison Study to Support Vector Machine

    Article • Neural Computation, August 2003, The MIT Press

    Professor Faming Liang

  70. Use of sequential structure in simulation from high-dimensional systems

    Article • May 2003, American Physical Society (APS)

    Professor Faming Liang

  71. Dynamically Weighted Importance Sampling in Monte Carlo Computation

    Article • Journal of the American Statistical Association, September 2002, Taylor & Francis

    Professor Faming Liang

  72. Some connections between Bayesian and non-Bayesian methods for regression model selection

    Article • Statistics & Probability Letters, March 2002, Elsevier

    Professor Faming Liang

  73. Evolutionary Monte Carlo for protein folding simulations

    Article • The Journal of Chemical Physics, August 2001, American Institute of Physics

    Professor Faming Liang

  74. Real-Parameter Evolutionary Monte Carlo With Applications to Bayesian Mixture Models

    Article • Journal of the American Statistical Association, June 2001, Taylor & Francis

    Professor Faming Liang

  75. A Theory for Dynamic Weighting in Monte Carlo Computation

    Article • Journal of the American Statistical Association, June 2001, Taylor & Francis

    Professor Faming Liang

  76. The Multiple-Try Method and Local Optimization in Metropolis Sampling

    Article • Journal of the American Statistical Association, March 2000, Taylor & Francis

    Professor Faming Liang

  77. Dynamic weighting Monte Carlo for constrained floorplan designs in mixed signal application

    Article • January 2000, ACM (Association for Computing Machinery)

    Professor Faming Liang

  78. Dynamic weighting in simulations of spin systems

    Article • Physics Letters A, March 1999, Elsevier

    Professor Faming Liang

  79. Relaxed simulated tempering for VLSI floorplan designs

    Article • January 1999, Institute of Electrical & Electronics Engineers (IEEE)

    Professor Faming Liang

  80. Stochastic Approximation Monte Carlo for MLP Learning

    Article • IGI Global

    Professor Faming Liang

  81. Dynamic weighting Monte Carlo for constrained floorplan designs in mixed signal application

    Article • Institute of Electrical & Electronics Engineers (IEEE)

    Professor Faming Liang