JSM2023
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Contributed Papers

Theory and Methods for Variable Selection

Thu, Aug 10, 8:30 AM
Fan DaiChair
Section on Statistical Learning and Data Science

6 Presentations

HRLR regression
8:35 AM - 8:50 AM
Lasanthi Pelawa Watagoda (Appalachian State University)
Co-authors: Hasthika Rupasinghe (Appalachian State University), Alan Arnholt (Appalachian State University)
Tuning Random Forests for Variable Importance
8:50 AM - 9:05 AM
Kelvyn Bladen
Co-authors: David Cutler (Utah State University)
Sufficient variable selection for ultrahigh dimensional right censored data via independence measure
9:05 AM - 9:20 AM
Qingcong Yuan (Sanofi)
Co-authors: Baoying Yang (Southwest Jiaotong University, China)
Subbagging Variable Selection for Massive Data
9:20 AM - 9:35 AM
Xian Li
Co-authors: Tao Zou (The Australian National University), Xuan Liang (Peking University)
Detection of Multiple Influential Observations on Variable Selection for High-dimensional Data
9:35 AM - 9:50 AM
Dongliang Zhang
Co-authors: Masoud Asgharian (McGill University), Martin Lindquist (Johns Hopkins University)
Model-Agnostic Feature Importance Inference: A Fast and Powerful Approach Using Minipatch Ensembles
9:50 AM - 10:05 AM
Lili Zheng
Co-authors: Luqin Gan, Genevera Allen (Rice University)

Session participants

Cheryl Brooks (AT&T Data Science and AI Research)
Participant
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