256
Mon, 7/29/2019,
2:00 PM -
3:50 PM
CC-Hall C
Contributed Poster Presentations: Section on Statistical Learning and Data Science — Contributed Poster Presentations
Section on Statistical Learning and Data Science , Text Analysis Interest Group
Chair(s): Wendy Meiring, University of California At Santa Barbara
65:
Accounting for Established Predictors with the Multi-Step Elastic Net
Elizabeth C Chase, University of Michigan ; Phil Boonstra, University of Michigan
66:
Big, Bad Matrices: a Constructive Approach
Garrett Mulcahy, Purdue University ; Thomas Sinclair, Purdue University
67:
Bimodal Sentiment Analysis of Service Calls
YANAN JIA, Businessolver
68:
Feature Selection for High-Dimensional Clustering by Hidden Markov Model with Variable Blocks(HMM-VB)
Beomseok Seo, Penn State University ; Jia Li, Penn State University; Lynn Lin, Penn State University
69:
On the Selection of Regression Model Using Machine Learning
Asanao Shimokawa, Tokyo University of Science ; Etsuo Miyaoka, Tokyo University of Science
70:
Training Students Concurrently in Data Science and Team Science: Results and Lessons Learned from Multi-Institutional Interdisciplinary Student-Led Research Teams 2012-2018
Brent Ladd, Purdue University ; Mark Ward, Purdue University
71:
Predicting Traffic Intensity with Deep Learning and Semantic Segmentation
Logan Bradley-Trietsch, Purdue University ; Xiao Wang, Purdue University
72:
Combining Machine Learning and Statistical Modeling to Identify Risk Factors of Hospital Mortality and Directionality for Patients with Acute Respiratory Distress Syndrome (ARDS)
Meng Zhang, Feinstein Institute for Medical Research ; Michael Qiu, Feinstein Institue for Medical Research; Molly Stewart, Feinstein Institue for Medical Research; Jamie Hirsch, Feinstein Institue for Medical Research; Negin Hajizadeh, Feinstein Institue for Medical Research
73:
Time Series Models to Forecast Mail Volume
Xuemei Pan ; Mary Pritts, IBM
75:
Testing Global Dynamics in C. Elegans
Anastasia Dmitrienko, Columbia University ; John Cunningham, Columbia University; Sean Bittner, Columbia University
76:
Testing for High-Dimensional Network Parameters in Auto-Regressive Models
Lili Zheng, University of Wisconsin-Madison ; Garvesh Raskutti, University of Wisconsin-Madison
77:
On the Non-Asymptotic and Sharp Lower Tail Bounds of Random Variables
Yuchen Zhou, University of Wisconsin-Madison ; Anru Zhang, University of Wisconsin-Madison
78:
A Computational Approach to the Structure of Subtraction Games
Kali Lacy, Purdue University ; Bret Benesh, College of Saint Benedict/Saint John's University; Jamylle Carter, Diablo Valley College; Deidra Coleman, Wofford College; Douglas Crabill, Purdue University; Jack Good, Purdue University; Michael Smith, Purdue University; Jennifer Travis, Lone Star College; Mark Ward, Purdue University
79:
Combining Materials and Data Science
Haydn Schroader, Purdue University ; Alejandro Strachan, Purdue University; Saaketh Desai, Purdue University; Juan Carlos Verduzco Gastelum, Purdue University; David Farache, Purdue University
80:
Computational and Theoretical Analysis of Novel Dimensionality Reduction Algorithms in Data Mining Brandon Guo
Brandon Guo
81:
A Natural Language Processing Algorithm for Medication Extraction from Electronic Health Records Using the R Programming Language: MedExtractR
Hannah L Weeks, Vanderbilt University ; Cole Beck, Vanderbilt University Medical Center; Elizabeth McNeer, Vanderbilt University; Joshua C Denny, Vanderbilt University; Cosmin A Bejan, Vanderbilt University; Leena Choi, Vanderbilt University Medical Center
82:
Question Answering Using a Domain Specific Knowledge Base
Mitchell Kinney, University of Minnesota - Twin Cities
83:
Propensity Score Analysis Using Machining Learning Techniques with Data Sets Involving Correlation of Covariates, Clustering, and Complex Outcome Functions and Propensity Scores
Li He, Clemson University ; William C. Bridges Jr., Clemson University
84:
Connecting Diverse Data with the Power of Natural Language Processing Methods
Tracy Schifeling, Bluprint ; Murat Tasan, Bluprint
85:
Performance of Latent Dirichlet Allocation with Different Topic and Document Structures
Haotian Feng, Clemson University
86:
Using Push-Forward and Pullback Measures for Parameter Identification and Distribution Estimation
Tian Yu Yen, University of Colorado At Denver ; Michael Pilosov, University of Colorado At Denver
87:
Using Machine Learning to Incorporate Nutrition into Cardiovascular Mortality Risk Prediction
Joseph Rigdon, Stanford University ; Sanjay Basu, Stanford University
88:
Gender Differences in Authorship of Invited Commentary Articles in Medical Journals
Emma Thomas, Harvard University ; Bamini Jayabalasingham, Elsevier, Inc.; Thomas Collins, Elsevier, Inc.; Jeroen Geertzen, Elsevier, Inc.; Chinh Bui, Elsevier; Francesca Dominici, Harvard T.H. Chan School of Public Health
89:
Open Category Detection with PAC Guarantees
Si Liu, Oregon State University ; Risheek Garrepalli, Oregon State University; Thomas G. Dietterich, Oregon State University; Alan Fern, Oregon State University; Dan Hendrycks, UC Berkeley
90:
Statistical Inference in a High-Dimensional Binary Regression Problem with Noisy Responses
Hyebin Song
91:
Personalized HeartSteps: a Reinforcement Learning Algorithm for Optimizing Physical Activity
Peng Liao, University of Michigan ; Susan Murphy, Harvard University; Predrag Klasnja, University of Michigan; Kristjan Greenewald, IBM
92:
Aggregated Single-Study Learners for Generalizable Predictions
Boyu Ren ; Lorenzo Trippa, Dana-Farber Cancer Institute; Giovanni Parmigiani, Dana-Farber Cancer Institute
93:
Recursive Optimization Using Diagonalized Hessian Estimate and Its Application in EM
Shiqing Sun ; James C. Spall, Applied Physics Laboratory
