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CC = Colorado Convention Center   H = Hyatt Regency Denver at Colorado Convention Center
* = applied session       ! = JSM meeting theme

Activity Details

353 Tue, 7/30/2019, 10:30 AM - 11:15 AM CC-Hall C
SPEED: Statistical Learning and Data Science Speed Session 2, Part 2 — Contributed Poster Presentations
Section on Statistical Learning and Data Science, Text Analysis Interest Group
Chair(s): Ali Shojaie, University of Washington
Oral Presentations for this session.
1: Three-Dimensional Radial Visualization of High-Dimensional Continuous or Discrete Data
Yifan Zhu, Iowa State University; Fan Dai, Iowa State University; Ranjan Maitra, Iowa State University
3: An Imputation Approach for Fitting Random Survival Forests with Interval-Censored Survival Data
Warren Keil; Tyler Cook, University of Central Oklahoma
4: Diagnostic Accuracy Evaluation of Diagnostic Assessment Model in Longitudinal Data: a Simulation Study of Neural Network Approach
Chi Chang, Michigan State University; Harlan McCaffery, University of Michigan
5: Smoothing Random Forest
Benjamin LeRoy, Carnegie Mellon University; Max G'Sell, Carnegie Mellon University
6: Aggregated Pairwise Classification of Statistical Shapes
Min Ho Cho, The Ohio State University
7: Statistical Optimality of Interpolated Nearest Neighbor Algorithms
Yue Xing, Purdue University; Qifan Song, Purdue University; Guang Cheng, Purdue Statistics
8: Ground Truth? Understanding How Humans Label Records and the Impact of Uncertainty
Kayla Frisoli, Carnegie Mellon University; Rebecca Nugent, Carnegie Mellon University
9: Block-Wise Partitioning for Extreme Multi-Label Classification
Yuefeng Liang, UC Davis; Thomas C. M. Lee, UC Davis; Cho-Jui Hsieh, UCLA
10: A Statistical Model for Tropical Cyclone Genesis and Assessing Its Differences Between Basins and Climates
Arturo Fernandez, University of California - Berkeley
11: Discovery of Gene Regulatory Networks Using Adaptively Selected Gene Perturbation Experiments
Michele Zemplenyi, Harvard University; Jeffrey Miller, Harvard TH Chan School of Public Health
12: Stagewise Generalized Estimating Equations for Varying Coefficient Models
Gregory Vaughan, Bentley University; Yicheng Kang, Bentley University
13: Stacked Ensemble Learning for Propensity Score Methods in Observational Studies
Maximilian Autenrieth, San Diego State University and Ulm University; Richard Levine, San Diego State University; Juanjuan Fan, San Diego State University; Maureen Guarcello, San Diego State University
14: Predicting Sub-Cellular Location of Plant Protein Using Supervised Machine Learning
David Arthur; Benjamin Annan, Youngstown State University; Eric Quayson, Youngstown State University; Jack Min, Youngstown State University; Guang-Hwa Andy Chang, Youngstown State University
15: Semi-Supervised, Dynamic Class-Informative Feature Learning
Vincent Pisztora