Contributed Papers

Statistical Methods for High-dimensional Data

Mon, Aug 4, 10:30 AM - 12:20 PM Room CC-103B Music City Center

Noah GadeChair

Section on Statistical Learning and Data Science

7 Presentations

A Debiased Estimator for the Mediation Functional in Ultra-High-Dimensional Setting in the Presence of Interaction Effects

10:35 AM - 10:50 AM

Co-authors: Shi Bo (Boston University), AmirEmad Ghassami (Boston University), Shi Bo (Boston University), Debarghya Mukherjee (Boston University)

Causal Mediation Analysis Debiased Estimation Ultra-High-Dimensional Models Interaction Effects

Advanced Survival Transformer for Integrating Multi-Omics Longitudinal Data with High-Dimensional Fe

10:50 AM - 11:05 AM

Co-authors: Yeji Kim (New York University, Division of Biotatistics, Department of Population Health), Jiyuan Hu (NYU Grossman School of Medicine), Yeji Kim (New York University, Division of Biotatistics, Department of Population Health)

Survival Analysis Transformer Deep Learning Covariate-dependent censoring High-dimensional longitudinal multi-omics Robust estimation

Envelope-Guided Regularization for Improved Prediction in High-Dimensional Multivariate Regression

11:05 AM - 11:20 AM

Co-authors: Tate Jacobson (Oregon State University), Oh-Ran Kwon, Tate Jacobson (Oregon State University)

double descent predictor envelopes principal components shrinkage estimator

REML estimators in High-Dimensional Kernel Linear Mixed Models

11:20 AM - 11:35 AM

Co-authors: Xiaoxi Shen (Texas State University), Qing Lu, Xiaoxi Shen (Texas State University)

Kernel Methods Inner Product Random Matrices Restricted Maximum Likelihood Estimator Consistency

Supervised Dimension Reduction for Regression Models with High-Dimensional Output

11:35 AM - 11:50 AM

Co-authors: Gavin Collins, Derek Tucker (Sandia National Laboratories), Gavin Collins, Carlos Llosa (Sandia National Laboratories)

Supervised Dimension Reduction High-Dimensional Response Nonlinear Regression

Tutorial: Differential Network Analysis with Application to High-Dimensional Biological Data

11:50 AM - 12:05 PM

Co-authors: Margaret Janiczek (University of Massachusetts, Amherst), Margaret Janiczek (University of Massachusetts, Amherst), Katherine Shutta (Harvard School of Public Health), Raji Balasubramanian (University of Massachusetts, Amherst)

graphical models biological pathway estimation differential network analysis Bayesian network estimation software application method overview

Ultra-High-Dimensional Mediation Analysis via Latent Factor Models with Interaction Effects

12:05 PM - 12:20 PM

Co-authors: Himani Yadav (Boston University), Shi Bo (Boston University), Himani Yadav (Boston University), Debarghya Mukherjee (Boston University), AmirEmad Ghassami (Boston University)

Latent Factors Mediation Analysis High-Dimensional Models Factor Model Diversified Projection Method