Contributed Papers

Statistical Learning Methods for Feature Selection & Model Tuning

Mon, Aug 4, 2:00 PM - 3:50 PM Room CC-101B Music City Center

Section on Statistical Computing

6 Presentations

A Framework for Comprehensive Model and Variable Selection

2:05 PM - 2:20 PM

Co-authors: Xiyue Liao (San Diego State University), Xiyue Liao (San Diego State University), Mary Meyer (Colorado State University)

variable selection shape and order constraints nonparametric nonadditive

A Generalized Extension of Finite Mixture Models

2:20 PM - 2:35 PM

Co-authors: Andrew Simpson (South Dakota State University), Semhar Michael (South Dakota State University), Andrew Simpson (South Dakota State University)

Clustering Classification Few-Shot Learning

SUPER: a tuning-free procedure for subgroup analysis

2:35 PM - 2:50 PM

Co-authors: Letian Li (University of Science and Technology of China), Daoji Li (California State University, Fullerton), Daoji Li (California State University, Fullerton), Jie Wu (Anhui University), Zemin Zheng (University of Science and Technology of China)

Subgroup analysis Heterogeneity Scale-invariance Tuning free Penalized fusion Statistical inference

Autotune: fast, efficient, and automatic tuning parameter selection for LASSO

2:50 PM - 3:05 PM

Co-authors: Tathagata Sadhukhan (Cornell University), Tathagata Sadhukhan (Cornell University), Sumanta Basu (Cornell University Department of Statistics and Data Science), Ines Wilms (Maastricht University), Stephan Smeekes (Maastricht University)

Tuning Biconvex Optimization Linear Models High Dimension Cross Validation Noise Variance

High-dimensional Inference for Sparse Vector Autoregression Processes

3:05 PM - 3:20 PM

Co-authors: Dananjani Madiwala Liyanage (University of Minnesota - Duluth), Dananjani Madiwala Liyanage (University of Minnesota - Duluth), Mihai Giurcanu (University of Chicago, Department of Public Health Sciences), Alexandre Trindade (Texas Tech University, Department of Mathematics & Statistics)

threshold estimation information criteria oracle property Granger-causality Sparse VAR

WITHDRAWN: Margin Weighted Robust Discriminant Score for Feature Selection in Imbalanced Gene Expression Class

3:20 PM - 3:35 PM

Co-authors: Saeed Aldahmani, Sheema Gul (Abdul University,), Zardad Khan

Classification High dimensional gene expression datasets Feature selection