Trevor Hastie

59 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0002-0164-3142

Department of Statistics, Stanford University

Publications

• A statistical view of column subset selection — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2025
• Cross-Validation: What Does It Estimate and How Well Does It Do It? — Journal of the American Statistical Association 2024
• Statistical curve models for inferring 3D chromatin architecture — The Annals of Applied Statistics 2024
• Surprises in high-dimensional ridgeless least squares interpolation — The Annals of Statistics 2022
• Generalized Matrix Factorization: efficient algorithms for fitting generalized linear latent variable models to large data arrays — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• LinCDE: Conditional Density Estimation via Lindsey's Method — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• Backfitting for large scale crossed random effects regressions — The Annals of Statistics 2022
• Large-scale multivariate sparse regression with applications to UK Biobank — The Annals of Applied Statistics 2022
• Discussion of “Prediction, Estimation, and Attribution” by Bradley Efron — Journal of the American Statistical Association 2020
• Confounder adjustment in multiple hypothesis testing — The Annals of Statistics 2017
• Saturating Splines and Feature Selection — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Effective degrees of freedom: a flawed metaphor — Biometrika 2015
• Customized training with an application to mass spectrometric imaging of cancer tissue — The Annals of Applied Statistics 2015
• Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares — Journal of Machine Learning Research 2015 (name-matched, not ORCID-linked)
• Local case-control sampling: Efficient subsampling in imbalanced data sets — The Annals of Statistics 2014
• Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife — Journal of Machine Learning Research 2014 (name-matched, not ORCID-linked)
• Finite-sample equivalence in statistical models for presence-only data — The Annals of Applied Statistics 2013
• Strong rules for discarding predictors in lasso-type problems — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2012
• Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso — Journal of Machine Learning Research 2012 (name-matched, not ORCID-linked)
• SparseNet: Coordinate Descent With Nonconvex Penalties — Journal of the American Statistical Association 2011
• Spectral Regularization Algorithms for Learning Large Incomplete Matrices — Journal of Machine Learning Research 2010 (name-matched, not ORCID-linked)
• Letters to the Editor — Journal of the American Statistical Association 2010
• Discussion — Journal of the American Statistical Association 2009
• New multicategory boosting algorithms based on multicategory Fisher-consistent losses — The Annals of Applied Statistics 2008
• “Preconditioning” for feature selection and regression in high-dimensional problems — The Annals of Statistics 2008
• L1-regularization path algorithm for generalized linear models — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2007
• Pathwise coordinate optimization — The Annals of Applied Statistics 2007
• Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections — Journal of Machine Learning Research 2007 (name-matched, not ORCID-linked)
• Margin Trees for High-dimensional Classification — Journal of Machine Learning Research 2007 (name-matched, not ORCID-linked)
• On the “degrees of freedom” of the lasso — The Annals of Statistics 2007
• Prediction by Supervised Principal Components — Journal of the American Statistical Association 2006
• Addendum: Regularization and variable selection via the elastic net — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2005
• Regularization and variable selection via the elastic net — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2005
• The Entire Regularization Path for the Support Vector Machine — Journal of Machine Learning Research 2004 (name-matched, not ORCID-linked)
• Boosting as a Regularized Path to a Maximum Margin Classifier — Journal of Machine Learning Research 2004 (name-matched, not ORCID-linked)
• Improved Semiparametric Time Series Models of Air Pollution and Mortality — Journal of the American Statistical Association 2004
• Discussions of boosting papers, and rejoinders — The Annals of Statistics 2004
• Least angle regression — The Annals of Statistics 2004
• Principal Component Analysis — Journal of the American Statistical Association 2003
• Degrees‐of‐freedom tests for smoothing splines — Biometrika 2002
• Functional linear discriminant analysis for irregularly sampled curves — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2001
• Estimating the number of clusters in a data set via the gap statistic — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2001
• Principal component models for sparse functional data — Biometrika 2000
• Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors) — The Annals of Statistics 2000
• Classification by pairwise coupling — The Annals of Statistics 1998
• Discriminant Analysis by Gaussian Mixtures — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 1996
• Pseudosplines — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 1996
• Penalized Discriminant Analysis — The Annals of Statistics 1995
• Discussion: The Use of Polynomial Splines and their Tensor Products in Multivariate Function Estimation — The Annals of Statistics 1994 (name-matched, not ORCID-linked)
• Flexible Discriminant Analysis by Optimal Scoring — Journal of the American Statistical Association 1994
• The Use of Polynomial Splines and Their Tensor Products in Multivariate Function Estimation — The Annals of Statistics 1994
• Varying-Coefficient Models — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 1993
• Principal Curves — Journal of the American Statistical Association 1989
• Linear Smoothers and Additive Models — The Annals of Statistics 1989
• Rejoinder: Linear Smoothers and Additive Models — The Annals of Statistics 1989
• Generalized Additive Models: Some Applications — Journal of the American Statistical Association 1987
• The Geometric Interpretation of Correspondence Analysis — Journal of the American Statistical Association 1987
• Local Likelihood Estimation — Journal of the American Statistical Association 1987
• Comment — Journal of the American Statistical Association 1984