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Activity Details

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