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Activity Details

184 Mon, 7/31/2017, 11:35 AM - 12:20 PM CC-Halls A&B
SPEED: Variable Selection and Networks — Contributed Poster Presentations
Section on Statistical Learning and Data Science
Chair(s): Jessi Cisewski, Yale University
The Speed portion will take place during Session 214519
2: A Robust Model-Free Feature Screening Method for Ultrahigh-Dimensional Data Jingnan Xue, Texas A&M University ; Faming Liang, University of Florida
3: Dynamic Latent Factor Modeling of UN Voting Networks Bomin Kim, Pennsylvania State University ; Xiaoyue Niu, Penn State University ; David Hunter, The Pennsylvania State University ; Xun Cao, The Pennsylvania State University
4: Variable Selection via Phony Variables Wenhao Hu, North Carolina State University ; Eric Laber, North Carolina State University ; Leonard Stefanski, North Carolina State University
5: Impact of Divergence of Training and Testing Sets on Predictive Risk and Measure of Model Complexity Jieyi Jiang, Ohio State University ; Yoonkyung Lee, The Ohio State University ; Steven MacEachern, The Ohio State University
6: Bayesian Adjustment for Confounding When Estimating Average Causal Effects for Time-To-Event Outcomes Li Xu ; Arnold Stromberg, Department of Statistics, University of Kentucky ; Chi Wang, Cancer Biostatistics, University of Kentucky
7: Efficient causal structure learning in high dimensions Arjun Sondhi, University of Washington ; Ali Shojaie, University of Washington
8: Assessing Variable Importance Nonparametrically Using Machine Learning Techniques Brian Williamson, University of Washington ; Marco Carone, University of Washington Department of Biostatistics ; Noah Simon, University of Washington ; Peter Gilbert, Fred Hutchinson Cancer Research Center
9: Varying-Coefficient Models for Dynamic Networks Jihui Lee, Columbia University ; Gen Li, Columbia University ; James D. Wilson, University of San Francisco
10: Parsimonious and Efficient Construction of Composite Likelihood Equations by L1-Penalization Zhendong Huang
11: Cross Validation for Penalized M-Estimation with a Case-Weight Adjusted Solution Path Shanshan Tu, The Ohio State University ; Yunzhang Zhu, Ohio State University ; Yoonkyung Lee, The Ohio State University
12: Finite Sample Estimation in General Vector Autoregressive Processes Mohamad Kazem Shirani Faradonbeh, University of Michigan ; Ambuj Tewari, University of Michigan ; George Michailidis, University of Florida
13: A Regularization Method for Detecting Differential Item Functioning Under the Framework of Generalized Linear Models Jing Jiang, Boston College ; Zhushan Li, Boston College
14: Collaborative Spectral Clustering in Attributed Networks Xiaodong Jiang ; Pengsheng Ji, University of Georgia
15: Structural Discovery in Temporal Networks Shaojun Zhang, University of Florida ; George Michailidis, University of Florida
16: Variable Selection for High-Dimensional Data via Generalized Penalty Mingwei Sun, University of Alabama ; Pu Patrick Wang, University of Alabama
17: Neighborhood Selection with Application to Social Networks Nana Wang ; Wolfgang Polonik, University of California, Davis
18: Detection of Treatment Effect After Variable Selection Under Model Misspecification Jingshen Wang, University of Michigan ; Xuming He, University of Michigan
19: Fostering Undergraduate Data Science Mark Ward, Purdue University ; Fulya Gokalp Yavuz, Purdue University and Yildiz Technical University
20: Model-Based Community Detection for Networks with Node Covariates Boang Liu, University of Michigan ; Ji Zhu, University of Michigan
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