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Activity Details

215 Tue, 8/4/2020, 10:00 AM - 2:00 PM Virtual
Contributed Poster Presentations: Section on Statistical Learning and Data Science — Contributed Poster Presentations
Section on Statistical Learning and Data Science
1: Identifying Pareto-Based Multiobjective Solutions for Subset Selection
Joshua Lambert, University of Cincinnati
2: Causal Effect Random Forest of Interaction Trees for Observational Data, Applied to Educational Interventions
Juanjuan Fan, San Diego State University; Luo Li, San Diego State University; Xiaogang Su, University of Texas, El Paso; Richard Levine, San Diego State University
3: Real-Time Classification of Atrial Fibrillation Using RR Intervals and Transition States
Jericho Lawson, University of Arizona
4: Statistical Invariance of Betti Numbers in the Thermodynamic Regime
Siddharth Vishwanath, Penn State Univ
5: Network Clustering with Entropy-Based Monte Carlo Method
Qiannan Zhai, Texas Tech University; Fangyuan Zhang, Texas Tech University
6: Context-Dependent Self-Exciting Point Processes: Models, Methods, and Risk Bounds in High Dimensions
Lili Zheng, University of Wisconsin-Madison; Garvesh Raskutti, UW-Madison; Rebecca Willett, University of Chicago
7: A Comparison of Machine Learning Models for Mortality Prediction: National Health and Nutrition Examination Survey (NHANES III)
Zoran Bursac, Florida International University; Roy Williams, Florida International University; Miguel Alonso, Florida International University; Prasad Bhoite, Florida International University; Emir Veledar, Florida International University
8: Incorporating Group Structure into Tree-Based Algorithms and Group Selection Through Importance Measures
Jiabei Yang, Brown University School of Public Health; Emily Dodwell, Data Science & AI Research, AT&T Labs; Ritwik Mitra, Data Science & AI Research, AT&T Labs; DeDe Paul, Data Science & AI Research, AT&T Labs
9: Stagewise Estimating Equations for Variable Selection with Longitudinal Rate Data
Gregory Vaughan, Bentley University
10: Weakly Supervised Chinese Meta-Pattern Discovery and NER via TopWORDS 2
Jiaze Xu, Tsinghua University; Ke Deng, Tsinghua University
11: Random-Projection Based Classification from Big Tensor Data
Peide Li
13: Connectivity Based Outlier Detection
Chang Liu, Rutgers University; Rong Chen, Rutgers University
14: An Algorithm for Adjusted Kernel Linear Discriminant Analysis
Lynn Huang, Iowa State University
15: Deriving and Generalizing Kernel Linear Discriminant Analysis for Multiple Cases
Jackson Maris
16: Adjusting Factor Models for Concomitant Variables by Adversarial Learning
Austin Talbot, Duke University; David Carlson, Duke University; David Dunson, Duke University
18: Covariance Estimation for Matrix-Variate Data with Missing Values and Mean Structure
Roger Fan, University of Michigan; Shuheng Zhou, University of California, Riverside; Byoungwook Jang, University of Michigan
19: Estimating Sleep from Sparse Screen-On/Screen-Off Smartphone Data
Melissa Martin, University of Pennsylvania
20: Robust Extrinsic Framework for Manifold Valued Data Analysis
Hwiyoung Lee, Florida State University
21: Clustering High Needs/Complex Patients Using Latent Class Analysis
Meghan Hatfield, Kaiser Permanente; Jodi McCloskey, Kaiser Permanente; Connie Uratsu, Kaiser Permanente; Richard Grant, Kaiser Permanente
22: SuperMICE: Multiple Imputation by Chained SuperLearners
Aaron Shev, University of California, Davis; Hannah Laqueur, University of California, Davis; Rose Kagawa, University of California, Davis
23: Feature Selection for Support Vector Regression Using a Genetic Algorithm
Shannon McKearnan, University of Minnesota; David Vock, University of Minnesota; Julian Wolfson, University of Minnesota
24: Time Varying Estimation of Tensor-On-Tensor Regression with Application in fMRI Data
Pratim Guha Niyogi, Michigan State University; Tapabrata (Taps) Maiti, Michigan State University
25: An Analytical Approach for Prediction Involving Classification of Data with Complex Structure
Li-Jung Liang, UCLA; Joseph Maurer, UCLA; Li Li, UCLA
26: Social Network Distributed Autoregressive Distributed Lag Model
Christopher Grubb, Virginia Tech; Shyam Ranganathan, Virginia Tech; Srijan Sengupta, Virginia Tech; Jennifer Van Mullekom, Virginia Tech
27: Assessment of Data Reduction Models Including Autoencoders for Optimal Visualization, Interpretability and Speed
Benedict Anchang, NIEHS
28: Aggregate Estimation in Sufficient Dimension Reduction for Binary Responses
Han Zhang, The University of Alabama; Qin Wang, The University of Alabama
29: Tensor Clustering with Planted Structures: Statistical Optimality and Computational Limits
Yuetian Luo, University of Wisconsin-Madison; Anru Zhang, University of Wisconsin-Madison
30: Augmented Movelet Method for Activity Recognition Using Smartphone Gyroscope and Accelerometer Data
Emily Huang, Wake Forest University Department of Mathematics and Statistics; Jukka-Pekka Onnela, Harvard University
31: Robust Matrix Estimations Meet Frank-Wolfe Algorithms
Naimin Jing, Temple University; Cheng Yong Tang, Temple University; Ethan Fang, Penn State University
32: Optimal Transport for Stationary Markov Chains
Kevin O'Connor, University of North Carolina, Chapel Hill; Andrew Nobel, University of North Carolina, Chapel Hill; Kevin McGoff, University of North Carolina, Charlotte
33: Early Prediction of Alzheimer’s Disease with Deep Learning Using Data Integration of MRI Data and Clinical Data
Lisa Neums, University of Kansas Medical Center; Jinxiang Hu, University of Kansas Medical Center; Jeffrey Thompson, University of Kansas Medical Center
34: Anomaly Detection Methods for IoT Freeze Loss
Patrick Toman, University of Connecticut - Department of Statistics; Ahmed Soliman, University of Connecticut; Nalini Ravishanker, University of Connecticut; Sanguthevar Rajasekaran, University of Connecticut; Nathan Lally, Hartford Steam Boiler; Yuchen Fama, Hartford Steam Boiler