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)
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
