F. Liang
Statistics and Probability · with Song · 2006–2013
A researcher in the Science corpus: 5 papers; trusts 33 researchers and is trusted by 40 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 33 citations into it; #5,321 of 12,932 by trust here, #7,508 by citations
- Artificial Intelligence — 12 citations into it
- Environmental Engineering — 12 citations into it; #276 of 5,479 by trust here, #1,201 by citations
- Economics and Econometrics — 8 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it; #1,039 of 1,525 by trust here, #1,365 by citations
- Optimization & Training — 5 citations into it; #1,680 of 2,601 by trust here, #2,378 by citations
Whom F. Liang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jianqing Fan
- Robert Tibshirani
- Michael L. Stein
- Yosihiko Ogata
- Stanley Wasserman
- John D. Storey
- Trevor J. Hastie
- Hui Zou
- Mário A. T. Figueiredo
- Michael Sherman
Who trusts F. Liang overall
- Angelo Mele
- Simo Särkkä
- M. Iglesias
- Andrew M. Stuart
- Liang Yan
- Frank Bauer
- Andrew J. Majda
- Luca Martino
- James Martin
- Kody J. H. Law
Papers from F. Liang's perspective
Ordered by how strongly the researchers F. Liang trusts endorse each paper. Same corpus, a different order for every researcher.
- Regression Shrinkage and Selection via the Lasso
- Addendum: Regularization and variable selection via the elastic net
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Estimating the Dimension of a Model
- Model selection and estimation in regression with grouped variables
- Sure independence screening for ultrahigh dimensional feature space
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Controlling the false discovery rate: a practical and powerful approach to multiple testing
- Sure independence screening for ultrahigh dimensional feature space Discussion
- Regularization Paths for Generalized Linear Models via Coordinate Descent
Their papers
- Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples (2010) — 244 citations
- A double Metropolis–Hastings sampler for spatial models with intractable normalizing constants (2010) — 169 citations
- Bayesian Subset Modeling for High-Dimensional Generalized Linear Models (2013) — 68 citations
- A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data (2013) — 84 citations
- Statistical and Computational Inverse Problems (2006) — 1,673 citations