181
Mon, 7/29/2019,
10:30 AM -
11:15 AM
CC-Hall C
SPEED: Statistical Learning and Data Science Speed Session 1, Part 2 — Contributed Poster Presentations
Section on Statistical Learning and Data Science
Chair(s): Ali Shojaie, University of Washington
Oral Presentations
for this session.
1:
Comparing Time Series Graphical Lasso and Sparse VAR Algorithms
Aramayis Dallakyan, Texas A&M University ; Rakheon Kim, Texas A&M University; Mohsen Pourahmadi, Texas A&M University
2:
Using Factor Analysis in Variable Selection and Clustering of US Mass Shooting Incidents
John McMorris ; Yew-Meng Koh, Hope College
3:
Model Selection for Mixture of Experts Using Group Fused Lasso
Tuan Do, University of South Carolina ; Karl Gregory, University of South Carolina
4:
Deep Learning and MARS: a Connection
Sophie Langer, Technische Universitaet Darmstadt ; Michael Kohler, Technische Universitaet Darmstadt; Adam Krzyzak, Concordia University
5:
Distance and Kernel Measures of Conditional Independence
Tianhong Sheng, The Pennsylvania State University ; Bharath Sriperumbudur, The Pennsylvania State University
6:
Sparse Functional Principal Component Analysis in High Dimensions
Xiaoyu Hu, peking university ; Fang Yao, peking university
7:
Activation Adaptation in Neural Networks
Vahid Partovi Nia, Huawei Technologies, Ecole Polytechnique de Montreal ; Farnoush Farhadi, Ericsson ; Andrea Lodi, Ecole Polytechnique de Montreal
8:
Multiple Imputation Versus Machine Learning: Predictive Models to Facilitate Analyzes of Association Between Contemporaneous Medicaid/CHIP Enrollment Status and Health Measures
Jennifer Rammon, National Center for Health Statistics/CDC ; Yulei He, CDC; Jennifer Parker, CDC/NCHS/OAE/SPB
9:
A Greedy-Type Variable Selection Procedure for Selecting High-Dimensional Cox Models
Chien-Tong Lin ; Yu-Jen Cheng, National Tsing Hua University; Ching-Kang Ing, National Tsin Hua University
10:
Cross-Validation for Correlated Data
Assaf Rabinowicz, Tel-Aviv University ; Saharon Rosset, Tel Aviv University
11:
Inference for Measurement Error Model Under High-Dimensional Settings
Mengyan Li, Penn State University ; Yanyuan Ma, The Pennsylvania State University
12:
Does T-SNE Identify False Structure? Implications of Clusterability on T-SNE Maps
Paul Harmon, Montana State University ; Mark Greenwood, Montana State University; Tristan Anacker, Montana State University
13:
Visual Diagnostics of a Model Explainer: Tools for the Assessment of LIME Explanations from Random Forests
Katherine Goode, Iowa State University ; Heike Hofmann, Iowa State University
14:
Quantile Regression Under Memory Constraint
Yichen Zhang, New York University ; Xi Chen, New York University; Weidong Liu, Shanghai Jiaotong University
15:
Equilibrium Metrics for Dynamic Supply-Demand Networks
Fan Zhou, University of North Carolina at Chapel Hill ; Hongtu Zhu, DiDi Chuxing and UNC-Chapel Hill; Jieping Ye, Didi Chuxing
16:
Topological Survival Analysis for the Comparison of Random Fields
Hollie Johnson
17:
Curve Registration to Identify Circadian Rhythm Chronotypes in Accelerometer Data
Erin McDonnell, Columbia University ; Julia Wrobel, Columbia University; Jeff Goldsmith, Columbia University; Vadim Zipunnikov, Johns Hopkins University
18:
Mallows Model Averaging of Support Vector Machine Classfiers and Regressors
Francis Kiwon, McMaster University
19:
To Select or Not to Select? Variable Selection in the Estimation of Drug Use Prevalence in Denmark
Anne Helby Petersen, University of Copenhagen ; Niels Keiding, University of Copenhagen
20:
Efficient Randomized Algorithms for Continuous Space Reinforcement Learning
Mohamad Kazem Shirani Faradonbeh, University of Florida ; Ambuj Tewari, University of Michigan; George Michailidis, University of Florida
