416
Thu, 8/12/2021,
2:00 PM -
3:50 PM
Virtual
SLDS CSpeed 7 — Contributed Speed
Section on Statistical Learning and Data Science
Chair(s): Danielle C. Tucker, University of Illinois at Chicago
2:05 PM
Efficient Designs of SLOPE Penalty Sequences in Finite Dimension
Yiliang Zhang, University of Pennsylvania ; Zhiqi Bu, University of Pennsylvania
2:10 PM
DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks
Shiyun Xu, University of Pennsylvania ; Zhiqi Bu, University of Pennsylvania
2:15 PM
Testing Joint Independence in High Dimensions
Faith Zhang, University of Massachusetts Amherst ; Maryclare Griffin, University of Massachusetts Amherst
2:20 PM
Doubly Robust Feature Selection with Mean and Variance Outlier Detection and Oracle Properties
Luca Insolia, Sant’Anna School of Advanced Studies ; Runze Li, Pennsylvania State University; Francesca Chiaromonte, Penn State University; Marco Riani, University of Parma
2:25 PM
Distribution-Free Bootstrap Prediction Intervals After Variable Selection
Hasthika Rupasinghe, Appalachian State University ; Lasanthi Watagoda, Appalachian State University
2:30 PM
Comparing Six Shrinkage Estimators with Large Sample Theory and Asymptotically Optimal Prediction Intervals
Lasanthi Watagoda, Appalachian State University ; David Olive, Southern Illinois University
2:35 PM
Inference Post-Selection of Group-Sparse Regression Models
Daniel Allan Kessler, University of Michigan ; Peter W. MacDonald, University of Michigan; Snigdha Panigrahi, University of Michigan
2:40 PM
Group Selection and Shrinkage with Application to Sparse Semiparametric Modeling
Ryan Thompson, Monash University ; Farshid Vahid, Monash University
2:45 PM
EAS Methodology for Grouped Variable Selection in Multivariate Linear Model
Salil Koner, North Carolina State University ; Jonathan P Williams, North Carolina State University
2:50 PM
Automatically Extracting Differential Equations from Data with Sparse Regression Techniques
Kevin Egan, Durham University ; Rui Carvalho, Durham University
3:00 PM
Canonical Correlation Analysis in High Dimensions with Structured Regularization
Elena Tuzhilina, Stanford University ; Leonardo Tozzi, Stanford University; Trevor JOHN Hastie, STANFORD UNIVERSITY
3:05 PM
Covariate-Assisted Sparse Tensor Completion and Inference
Hilda Somnooma Ibriga, Purdue University ; Will Wei Sun, Purdue University
3:10 PM
Computationally Sufficient Reductions for Some Sparse Multi-Way and Matrix-Variate Estimators
Prateek Sasan, The Ohio State University ; Akshay Prasadan, Carnegie Mellon University; Vincent Q Vu, The Ohio State University
3:15 PM
High-Dimensional Factor Analysis for Network-Linked Data
Jinming Li, University of Michigan ; Gongjun Xu, University of Michigan; Ji Zhu, University of Michigan
3:20 PM
Sparse Envelope Quantile Regression
Lawrence Segbehoe, South Dakota State University ; Gemechis Djira, South Dakota State Unversity; Hossein Moradi Rekabdarkolaee, South Dakota State University
3:25 PM
An Investigation of the False Discovery Rate Under Weak Dependency
Andrew Bartlett, Southern Connecticut State University
3:30 PM
A Univariate Approach to High-Dimensional Linear Regression via a Quasi-EM Algorithm
Alexander McLain, University of South Carolina ; Anja Zgodic, University of South Carolina; Joshua Habiger, Oklahoma State University
3:35 PM
A Sampling-Based Principal Component Analysis Procedure for Interpretable Representations of a Network Sample
James D. Wilson, University of San Francisco ; Jihui Lee, Weill Medical College of Cornell University
3:40 PM
Comparison of Change Point Detection Methods for Independent Data: Testing & Estimation
Casey Christiansen, Western Washington University
