Sufficient Dimension Reduction: An Information-Theoretic Viewpoint

On order determination by predictor augmentation

(2020) Wei Luo et al.   BIOMETRIKA

Real-time sufficient dimension reduction through principal least squares support vector machines

(2020) Andreas Artemiou et al.   PATTERN RECOGNITION

Assumption Lean Regression

(2019) Richard Berk et al.   AMERICAN STATISTICIAN

On the information bottleneck theory of deep learning

(2019) Andrew M Saxe et al.   JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT

A unified approach to sufficient dimension reduction

(2018) Yuan Xue et al.   JOURNAL OF STATISTICAL PLANNING AND INFERENCE

Covariate Information Matrix for Sufficient Dimension Reduction

(2018) Weixin Yao et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Combining eigenvalues and variation of eigenvectors for order determination

(2016) Wei Luo et al.   BIOMETRIKA

Controlling the false discovery rate via knockoffs

(2015) Rina Foygel Barber et al.   ANNALS OF STATISTICS

Dimension reduction based on the Hellinger integral

(2014) Q. Wang et al.   BIOMETRIKA

A general theory for nonlinear sufficient dimension reduction: Formulation and estimation

(2013) Kuang-Yao Lee et al.   ANNALS OF STATISTICS

Principal support vector machines for linear and nonlinear sufficient dimension reduction

(2012) Bing Li et al.   ANNALS OF STATISTICS

Buprenorphine/Naloxone and methadone effects on laboratory indices of liver health: A randomized trial

(2012) Andrew J. Saxon et al.   DRUG AND ALCOHOL DEPENDENCE

Kernel dimension reduction in regression

(2009) Kenji Fukumizu et al.   ANNALS OF STATISTICS

Successive direction extraction for estimating the central subspace in a multiple-index regression

(2008) Xiangrong Yin et al.   JOURNAL OF MULTIVARIATE ANALYSIS

An Informational Measure of Association and Dimension Reduction for Multiple Sets and Groups With Applications in Morphometric Analysis

(2008) Ross Iaci et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION