Online Program Home
My Program

Sessions Were Renumbered as of May 19.

Legend:
CC-W = McCormick Place Convention Center, West Building,   CC-N = McCormick Place Convention Center, North Building
H = Hilton Chicago,   UC= Conference Chicago at University Center
* = applied session       ! = JSM meeting theme

Activity Details

73 Sun, 7/31/2016, 4:00 PM - 5:50 PM CC-W186a
Resistant and Outlier-Robust Methods — Contributed Papers
Section on Statistical Learning and Data Science
Chair(s): Carolyn Bradshaw Morgan, Hampton University
4:05 PM Using L_1 Data Depth Unsupervised Classifier for Detecting Communities in Networks Yahui Tian ; Yulia R. Gel, The University of Texas at Dallas
4:20 PM Fast and Robust Vertex Classification by Sequential Screening Li Chen, Intel Corporation ; Cencheng Shen, Temple University ; Carey Priebe, The Johns Hopkins University
4:35 PM Efficient Robust Regression with Variable Selection via Generalized Empirical Likelihood Sohini Raha, North Carolina State University ; Howard Bondell, North Carolina State University
4:50 PM Asymptotic Relative Efficiency for Robust Estimation of the Mean of Contaminated Graphs Under a Low Rank Model Runze Tang, The Johns Hopkins University ; Minh Tang, The Johns Hopkins University ; Michael Ketcha, The Johns Hopkins University ; Carey Priebe, The Johns Hopkins University ; Joshua Vogelstein, The Johns Hopkins University
5:05 PM Fully Efficient and Outlier-Robust Estimation in the Linear Mixed Model Won Gyo Suh, North Carolina State University ; Howard Bondell, North Carolina State University
5:20 PM A Model-Selection Criterion for Regression Estimators Based on Data Depth Subhabrata Majumdar, University of Minnesota - Twin Cities ; Snigdhansu Chatterjee, University of Minnesota - Twin Cities
5:35 PM Robust Clustering Methods for Time-Evolving Brain Signals Tianbo Chen, KAUST ; Ying Sun, King Abdullah University of Science and Technology ; Carolina Euan, CIMAT ; Hernando Ombao, University of California at Irvine
 
 
Copyright © American Statistical Association