Keyword Search
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Keyword Search Criteria: Learning returned 156 record(s)
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Sunday, 07/30/2017
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The Geometry of Synchronization Problems and Learning Group Actions
Tingran Gao, Duke University; Jacek Brodzki, University of Southampton; Sayan Mukherjee, Duke University
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Sufficient Markov Decision Processes with Alternating Deep Neural Networks
Longshaokan Wang, North Carolina State University; Eric Laber, North Carolina State University; Katie Witkiewitz, University of New Mexico
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Optimal Dynamic Treatment Regimes Using Decision Lists
Yichi Zhang, Harvard University; Eric Laber, North Carolina State University; Anastasios (Butch) Tsiatis, North Carolina State University; Marie Davidian, North Carolina State University
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Transforming Undergraduate Statistics Education Through Experiential Learning: It's Essential!
Tracy Morris, University of Central Oklahoma; Cynthia Murray, University of Central Oklahoma; Tyler Cook, University of Central Oklahoma
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Computational Health Economics for Health Care Spending
Sherri Rose, Harvard Medical School; Savannah Bergquist, Harvard University; Tim Layton, Harvard Medical School
2:05 PM
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Matched Learning (M-Learning) for Estimating Optimal Individualized Treatment Rules
Peng Wu, Columbia University; Yuanjia Wang , Columbia University
2:05 PM
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The Use of Artificial Neural Network in Time Series Forecasting
Taysseer Sharaf, University of Michigan- Dearborn
2:20 PM
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Determining Personalized Dosing Intervals
Xiaomao Li, university of wisconsin-madison; Jun Shao, university of wisconsin-madison; Menggang Yu, university of wisconsin-madison
2:35 PM
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Constant-Gain Stochastic Gradient Algorithm in Nonstationary Environment
Jingyi Zhu, Johns Hopkins University Applied Mathematics and Statistics; James C Spall, Applied Physics Laboratory
2:35 PM
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Scalable Bayesian Learning for Sparse Logistic Models
Xichen Huang; Feng Liang, University of Illinois at Urbana Champaign
2:45 PM
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New Problem Settings for Predictive Modeling of High-Dimensional Data
Vladimir Cherkassky, University of Minnesota
2:55 PM
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Classification Using Ensemble Learning Under Weighted Misclassification Loss
Yizhen Xu, Brown University; Tao Liu, Brown University, Dept of Biostatistics; Rami Kantor , Brown Univeresity School of Medicine; Ann Mwangi, Moi University; Michael J Daniels, University of Texas at Austin; Joseph Hogan, Brown University, Dept of Biostatistics
3:05 PM
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Tree Based Weighted Learning for Estimating Individualized Treatment Rules with Censored Data
Yifan Cui, University of North Carolina at Chapel Hill; Ruoqing Zhu, University of Illinois Urbana-Champaign; Michael R Kosorok, University of North Carolina at Chapel Hill
3:20 PM
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Estimation of Henze-Penrose Mutual Information via Minimal Spanning Trees
Salimeh Yasaei Sekeh, EECS, University of Michigan ; Alfred Hero, EECS, University of Michigan
3:20 PM
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Combining Unit Root Tests with Machine Learning Techniques
Edward Herranz; James Gentle, George Mason University
3:35 PM
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Automated Learning Techniques for Electronic Health Record (EHR) Unstructured Notes
Michael Sanky, Optum; Balaji Ramesh, Optum
4:05 PM
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Local Nearest Neighbour Classification with Applications to Semi-Supervised Learning
Timothy I. Cannings, Universtiy of Southern California; Thomas Berrett, University of Cambridge; Richard J. Samworth, Statistical Laboratory, University of Cambridge
4:05 PM
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Latent Dirichlet Allocation Topic Models Applied to the Centers for Disease Control and Prevention's Grant Portfolio
Matthew Eblen, Centers for Disease Control and Prevention; Robin Wagner, Centers for Disease Control and Prevention
4:05 PM
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Sequential Outcome-Weighted Multicategory Learning for Estimating Optimal Individualized Treatment Rules
Xuan Zhou
4:20 PM
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An Active Learning Approach to Record Linkage
Kayla Frisoli, Carnegie Mellon University; Sam Ventura, Carnegie Mellon University; Jared S Murray, Carnegie Mellon University; Stephen Fienberg, Carnegie Mellon University
4:20 PM
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Identifying Out of Business Records on the NASS List Frame Using Boosted Regression Trees
Gavin Corral, USDA NASS; Andrew Dau, USDA NASS
4:20 PM
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Moralization and Interventions for DAG Model Learning
Gunwoong Park, University of Michigan
4:50 PM
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Multivariate Gaussian Network Structure Learning
Xingqi Du, North Carolina State University; Subhashis Ghoshal, North Carolina State University
5:05 PM
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Exploration of Innovating Business with Analytics
Mingfei Li, Bentley University
5:25 PM
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Monday, 07/31/2017
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Identifying clusters of cognitive functioning trajectories in elderly: A comparison of three methodologies
Victor Talisa, Department of Biostatistics, University of Pittsburgh; Tianxiu Wang, University of Pittsburgh; Zhongying Xu, University of Pittsburgh; Joyce Chang, University of Pittsburgh
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RGalleon.Com: a Resource for Non-Programmers to Learn R
William Lamberti, George Mason Univ
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Extending the Distributed Lag Model Framework to Evaluate Mixture Effects - a Nonparametric Approach
Ghalib Bello, Icahn School of Medicine at Mount Sinai
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Analysis of Student Learning, Comparing Traditional Vs Flipped Teaching in College Elementary Statistics
Dilrukshika Singhabahu, Slippery Rock University
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Initial Findings About Graduate Teaching Assistants' Training Needs to Foster Active Learning in Statistics
Kristen Roland; Jennifer Kaplan, University of Georgia
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Batch Policy Evaluation for Average Reward
Peng Liao; Susan A Murphy, University of Michigan
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AN ANALYSIS of NETWORK DISCUSSION TRENDS in TWITTER USING HASHTAG CLUSTERS
Elizabeth Tigner, Purdue University ; Jennifer Neville, Purdue University
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Leveraging Ensembles of Machine Learning Algorithms to Provide Real-Time Instructor Feedback
Alexander Lyford, UGA
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Using Statistical Learning to Develop a More Sensitive Outcome for Progressive Multiple Sclerosis
Christopher Barbour, Montana State University; Mark Greenwood, Montana State University; Peter Kosa, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Danish Ghazali, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Makoto Tanigawa, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Blake Snyder, National Institute of Neurological Disorders and Stroke, National Institutes of Health; Bibiana Bielekova, National Institute of Neurological Disorders and Stroke, National Institutes of Health
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CAM2 Network Camera Object Detection Dataset and Analysis
Kent Gauen, Purdue University; Yuxiang Zi, Purdue University; John Laiman, Purdue University; Nirmal Asokan, Purdue University; Yung-Hsiang Lu, Purdue University
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Data Science and Environmental Statistics
Stephan Sain, Unaffiliated
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A Generalizable Application of SuperLearner to Facial Recognition
Mary Combs, UNIVERSITY OF CALIFORNIA
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An Algorithm for Detecting Melanoma Based on Imaging Biomarkers
Joel Correa da Rosa, Rockefeller University; Amanda Zong, The Rockefeller University; Daniel Gareau, The Rockefeller University
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Bayesian Methods for Image Texture Analysis with Applications to Cancer Radiomics
Xiao Li, University of Texas, School of Public Health, Department of Biostatistics; Michele Guindani, University of California, Irvine; Chaan Ng, The University of Texas MD Anderson C; Brian P. Hobbs, The University of Texas MD Anderson Cancer Center
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Efficient causal structure learning in high dimensions
Arjun Sondhi, University of Washington; Ali Shojaie, University of Washington
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Assessing Variable Importance Nonparametrically Using Machine Learning Techniques
Brian Williamson, University of Washington; Marco Carone, University of Washington Department of Biostatistics; Noah Simon, University of Washington; Peter Gilbert, Fred Hutchinson Cancer Research Center
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Deep Learning Econometrics
Guanhao Feng; Nicholas Polson, University of Chicago; Jianeng Xu, University of Chicago
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A Case Study in Adaptive LASSO Logistic Regression: Factors Related to Cyclist Death When Drivers Are Distracted
Lysbeth Floden, University of Arizona; Patrick Anthony O'Connor, University of Arizona; Melanie Bell, University of Arizona
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An Overview of Existing and a Novel Approaches to Multi-Label Classification
Hyukjun Gweon; Matthias Schonlau, University of Waterloo; Stefan Steiner, University of Waterloo
8:35 AM
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On Reject and Refine Options in Multicategory Classification
Chong Zhang, Seattle, Washington ; Wenbo Wang, Binghamton University; Xingye Qiao, Binghamton University
8:55 AM
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Efficient causal structure learning in high dimensions
Arjun Sondhi, University of Washington; Ali Shojaie, University of Washington
9:05 AM
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Assessing Variable Importance Nonparametrically Using Machine Learning Techniques
Brian Williamson, University of Washington; Marco Carone, University of Washington Department of Biostatistics; Noah Simon, University of Washington; Peter Gilbert, Fred Hutchinson Cancer Research Center
9:10 AM
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Delayed Greedy Algorithm for Classification and Regression Trees
Kyle Caudle, South Dakota School of Mines and Technology; Larry Pyeatt, South Dakota School of Mines and Technology; Patrick Fleming, South Dakota School of Mines and Technology
9:20 AM
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Empirical Bayes Learning from Co-Data in High-Dimensional Prediction Settings
Mark Van De Wiel, VU University medical center
9:35 AM
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SVM-CART for Disease Classification
Evan Reynolds, University of Michigan; Mousumi Banerjee, University of Michigan; Brian Callaghan, University of Michigan
9:35 AM
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Learning Non-Parametric Binary Regression Using Flixible Power Link Function with GP Priors
Abhishek Bishoyi, University of Connecticut; Xiaojing Wang, University of Connecticut; Dipak K Dey, university of connecticut
9:35 AM
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Sample Size Methods for Developing Predictors from Genomic Data
Kevin Dobbin, University of Georgia
10:35 AM
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There Has to Be an Easier Way: a Simple Alternative for Parameter Tuning of Supervised Learning Methods
Jill Lundell
10:35 AM
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Sending Analysis to the Data: Optimizing Information Exchange in the Learning Health Care System
Darren Toh, Harvard Medical School and Harvard Pilgrim Health Care Institute
11:00 AM
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On Data Integration Problems with Manifolds
Kenneth Ryan, WVU; Mark Culp, West Virginia University
11:05 AM
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Implementing Active Learning in an Undergraduate Statistics Classroom
Elizabeth Jennings McGuffey, United States Naval Academy
11:05 AM
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Learning Causal Networks via Additive Faithfulness
Kuang-Yao Lee, Yale University; Tianqi Liu, Yale University; Bing Li, Pennsylvania State University; Hongyu Zhao, Yale University
11:15 AM
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Bayesian Methods for Image Texture Analysis with Applications to Cancer Radiomics
Xiao Li, University of Texas, School of Public Health, Department of Biostatistics; Michele Guindani, University of California, Irvine; Chaan Ng, The University of Texas MD Anderson C; Brian P. Hobbs, The University of Texas MD Anderson Cancer Center
11:20 AM
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Enhancing Instruction: Preparing Graduate Teaching Assistants for Active Learning
Jennifer Green, Montana State University; Elizabeth Arnold, Montana State University
11:20 AM
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Classification Using the Morlet Transform for fMRI Data
Debashis Ghosh, Colorado School of Public Health; Manish Dalwani, Colorado School of Medicine
11:25 AM
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Computational Learning Methods for Neuroimaging Data Analysis
Don Hong, Middle Tennessee State Univ; Xin Yang, Southern Arkansas University; Jingsai Liang, Middle Tennessee State University
11:35 AM
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A Case Study in Adaptive LASSO Logistic Regression: Factors Related to Cyclist Death When Drivers Are Distracted
Lysbeth Floden, University of Arizona; Patrick Anthony O'Connor, University of Arizona; Melanie Bell, University of Arizona
11:40 AM
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Statisticians Leading the Way: Advocating for Learning Health Systems and Collaborating Effectively with Clinical Stakeholders
Rebecca Yates Coley, Kaiser Permanente Washington Health Research Institute; Scott Zeger, Johns Hopkins University
11:50 AM
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Deep Learning Econometrics
Guanhao Feng; Nicholas Polson, University of Chicago; Jianeng Xu, University of Chicago
11:50 AM
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Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models
Daniel Apley, Northwestern University
11:50 AM
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Assessment of Impact of Using Learning Assistants in an Introductory Statistics Course
Jeff Kollath, Oregon State University
11:50 AM
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Providing Consulting Experiences Through Role Playing in a Graduate Statistics Course
Roy T Sabo, Virginia Commonwealth University
2:05 PM
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D-Learning to Estimate Optimal Individual Treatment Rules
Zhengling Qi, University of North Carolina, Chapel Hill; Yufeng Liu, University of North Carolina
2:20 PM
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Individualized Multilayer Tensor Learning with an Application in Imaging Analysis
Xiwei Tang, University of Illinois at Urbana-Champaign; Xuan Bi, Yale University; Annie Qu, University of Illinois at Urbana-Champaign
3:25 PM
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Microbiome Data Classification Under Sampling Zeros
Zachary Kurtz; Christian Müller, Flat Iron Institute, Simons Foundation; Richard Bonneau, Flat Iron Institute, Simons Foundation
3:25 PM
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Tuesday, 08/01/2017
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Medicare Risk Adjustment with Systematically Missing Data
Savannah Bergquist, Harvard University; Tim Layton, Harvard Medical School; Thomas G. McGuire, Harvard Medical School; Sherri Rose, Harvard Medical School
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Why Do Students Hate Statistics?
Michael DeDonno, Florida Atlantic University
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Precision Medicine Opportunities in Mental Health
Michael R Kosorok, University of North Carolina at Chapel Hill
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Three Methods for Occupation Coding Based on Statistical Learning
Matthias Schonlau, University of Waterloo; Hyukjun Gweon; Lars Kaczmirek, GESIS; Michael Blohm, GESIS; Stefan Steiner, University of Waterloo
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Integrating Data Science and Big Data Concepts and Machine Learning in Drug Safety
Melvin Munsaka, Safety Statistics and Observational Res Analytics, Takeda
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Using Data Mining to Identify At-Risk Freshmen
Nora Galambos, Stony Brook University
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Variable Selection on Functional Data Using Kernel Machine
Haoyu Wang, North Carolina State University
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Robust Feature Selection and Cell Line Classification with Electric Cell-Substrate Impedance Sensing Data
Megan Gelsinger, Cornell University; David S Matteson, Cornell University; Laurie Tupper, Williams College
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Learning from Imbalanced Data: a Review of Some Existing Methodologies
Josephine Akosa, Oklahoma State University; Melinda McCann, Oklahoma State University
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Learning Statistics with Productive Practice and Technology
Brenda Gunderson, Univ of Michigan
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Developing a Performance Sustaining Decoder for a Brain Computer Interface Controlled Neuroprosthetic Device
David Friedenberg, Battelle Memorial Institute; Mingming Zhang, Battelle; Michael Schwemmer, Battelle; Nick Annetta, Battelle; Marcia Bockbrader, Center for Neuromodulation, The Ohio State University & Department of Physical Medicine an; Chad Bouton, Battelle (currently at Feinstein Institute for Medical Research); Ali Rezai, Center for Neuromodulation, The Ohio State University; W. Jerry Mysiw, Department of Physical Medicine and Rehabilitation, The Ohio State University ; Herbert Bresler, Battelle; Gaurav Sharma, Battelle
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Three Principles for Data Science: Predictability, Stability and Computability
Bin Yu, University of California, Berkeley
8:35 AM
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Robust Feature Selection and Cell Line Classification with Electric Cell-Substrate Impedance Sensing Data
Megan Gelsinger, Cornell University; David S Matteson, Cornell University; Laurie Tupper, Williams College
8:50 AM
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Stability, Uncertainty, and Bayesian Learning
Chris Holmes, University of Oxford
9:00 AM
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Development of a Multi-Parametric MR Classifier for Prostate Cancer
Joseph Koopmeiners, University of Minnesota; Jin Jin, University of Minnesota; Lin Zhang, University of Minnesota; Ethan Leng, University of Minnesta; Greg Metzger, University of Minnesta
9:00 AM
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Adaptive Ensemble Kalman Filters for Online Bayesian State and Parameter Estimation
Jonathan Stroud, Georgetown University; Matthias Katzfuss, Texas A&M University; Christopher Wikle, University of Missouri
9:15 AM
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Learning heterogeneity in causal inference using sufficient dimension reduction
Wenbo Wu, University of Oregon; Wei Luo, Baruch College; Yeying Zhu, University of Waterloo
9:25 AM
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Structural Image Analysis for Improved Prediction of Patient Outcomes
Ani Eloyan, Brown University
9:25 AM
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Modeling Weather-Induced Home Insurance Risks with Support Vector Machine Regression
Vyacheslav Lyubchich, University of Maryland Center for Environmental Science; Yulia R. Gel, University of Texas at Dallas; Asim Kumer Dey, University of Texas at Dallas
9:35 AM
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Variable Selection on Functional Data Using Kernel Machine
Haoyu Wang, North Carolina State University
10:40 AM
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Research Findings on Innovative Teaching Methods in Statistics Classes Using ALEKS
Cheng Li; Xiaohui Wang, University of Texas Rio Grande Valley
10:50 AM
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Metagenomic Meta-Analysis of Large Data Sets: Tools and Biological Insights
Edoardo Pasolli, University of Trento, CIBIO
10:55 AM
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Individualized Fusion Learning (IFusion) with Applications to Personalized Inference
Minge Xie, Rutgers University; Jieli Shen, Rutgers University; Regina Liu, Rutgers University
11:00 AM
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Causal Structure Learning in High-Dimensional Settings
Preetam Nandy, University of Pennsylvania
11:05 AM
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Learning from Imbalanced Data: a Review of Some Existing Methodologies
Josephine Akosa, Oklahoma State University; Melinda McCann, Oklahoma State University
11:05 AM
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Learning Statistics with Productive Practice and Technology
Brenda Gunderson, Univ of Michigan
11:05 AM
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Improving Statistics Education Through Interactive Learning Tools
Philipp Burckhardt, Carnegie Mellon University; Alexandra Chouldechova, Carnegie Mellon University
11:05 AM
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A Collaboration with Four-Year Institution and Community College Faculty to Engage Students in Learning Statistics
Ginger Rowell, Middle Tennessee State University; Lisa Green, Middle Tennessee State University; Nancy McCormick, Middle Tennessee State University; Scott McDaniel, Middle Tennessee State University; Jeremy Strayer, Middle Tennessee State University; Marilee Gorta, Columbia State Community College; Lori Giles, Columbia State Community College; James Smith, Columbia State Community College; Michael Darrell, Columbia State Community College
11:20 AM
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Developing a Performance Sustaining Decoder for a Brain Computer Interface Controlled Neuroprosthetic Device
David Friedenberg, Battelle Memorial Institute; Mingming Zhang, Battelle; Michael Schwemmer, Battelle; Nick Annetta, Battelle; Marcia Bockbrader, Center for Neuromodulation, The Ohio State University & Department of Physical Medicine an; Chad Bouton, Battelle (currently at Feinstein Institute for Medical Research); Ali Rezai, Center for Neuromodulation, The Ohio State University; W. Jerry Mysiw, Department of Physical Medicine and Rehabilitation, The Ohio State University ; Herbert Bresler, Battelle; Gaurav Sharma, Battelle
11:20 AM
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Predicting Industry Output with Statistical Learning Methods
Peter Meyer, U.S. Bureau of Labor Statistics; Wendy Martinez, Bureau of Labor Statistics
11:20 AM
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Statistical Machine Learning and Precision Medicine
Michael Lawson, University of North Carolina at Chapel Hill; Michael R Kosorok, University of North Carolina at Chapel Hill
11:25 AM
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Predictive Analytics in Industrial Asset Health Management
Wenyu Zhao, Schlumberger
11:35 AM
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Evaluating Change in Learning from Different Forms of Interactive Visualizations with a Large Case Study.
Lata Kodali; Peter Hauck , Virginia Tech, Discovery Analytics Center; Michelle Dowling, Virginia Tech, Department of Computer Science; Leanna House, Virginia Tech, Department of Statistics; Scotland Leman, Virginia Tech; Chris North, Virginia Tech, Department of Computer Science
11:35 AM
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Hypothesis testings on high-dimensional individualized treatment rules
Young-Geun Choi, Fred Hutchinson Cancer Research Center; Yang Ning, Cornell University; Yingqi Zhao, Fred Hutchinson Cancer Research Center
11:50 AM
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Using Data Mining to Identify At-Risk Freshmen
Nora Galambos, Stony Brook University
12:05 PM
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Machine Learning Methods to Improve Causal Inference
Elizabeth Stuart, Johns Hopkins University
2:05 PM
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Adventures in Statistical Machine Learning
Grace Wahba, University of Wisconsin
2:05 PM
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Predictive Modeling of Health Care Associated Infections (HAIs) Using National Linked Individual Health Care Data in Scotland
Kimberley Kavanagh, University of Strathclyde; Jiafeng Pan, University of Strathclyde; Chris Robertson, University of Strathclyde; Marion Bennie, University of Strathclyde; Charis Marwick, University of Dundee; Colin McCowan, University of Glasgow
2:20 PM
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Learning with Latent Trajectory Classes
Chen-Pin Wang, UTHSCSA; Booil Jo, Stanford University
2:25 PM
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Teaching Statistical Collaboration Classes in Sequence
Dandan Liu, Vanderbilt University; Mario Davidson, Vanderbilt University
2:25 PM
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The Estimation of Match Validity Under the Fellegi-Sunter Paradigm Without Assuming Identifier-Agreement Independence
Dean Resnick, NORC
2:25 PM
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Predicting Market Segment Membership Using Deep Learning
Lynd Bacon, LBA Ltd. | Northwestern Univ. | Notre Dame Univ.
2:35 PM
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A Bayesian Mallows Approach to Non-Transitive Pair Comparison Data: How Human Are Sounds?
Marta Crispino, Bocconi University; Natasha Barrett, Norges musikkhøgskole; Arnoldo Frigessi, OCBE, UiO; Elja Arjas, University of Helsinki, & OCBE, UiO; Valeria Vitelli, University of Oslo
2:35 PM
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Statistical Collaboration: Experiential and Case Study Based Teaching Approaches
Trupti Trivedi, Drexel University/Adaptimmune LLC
2:45 PM
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Hypothesis Testing for Nonlinear Feature Interaction Using Cross-Validated Kernel Ensemble
Jeremiah Zhe Liu, Harvard University; Brent Coull, Harvard T.H. Chan School of Public Health
3:20 PM
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Wednesday, 08/02/2017
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Regression-Enhanced Random Forests
Haozhe Zhang, Iowa State University; Dan Nettleton, Iowa State University; Zhengyuan Zhu, Iowa State University
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Bernstein and Hoeffding Type Inequalities for Regenerative Markov Chains
Gabriela Cio?ek, Telecom ParisTech; Patrice Bertail, Université Paris Ouest Nanterre
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Group Fused Multinomial Regression
Brad Price, West Virginia University; Adam Rothman, University of Minnesota; Charles Geyer, University of Minnesota
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Building Comprehensive Searches Through a Machine Learning Approach for Systematic Reviews
Corrado Lanera, University of Padova; Ileana Baldi, University of Padova; Clara Minto, University of Padova; Dario Gregori, University of Padova; Paola Berchialla, University of Torino
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Personalizing Mobile Health Interventions
Susan A Murphy, University of Michigan
8:35 AM
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Data-Adaptive Statistics for Multiple Hypothesis Testing in High-Dimensional Settings
Weixin Cai, University of California, Berkeley; Alan Hubbard, University of California, Berkeley
8:35 AM
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A Parallel EM Algorithm for Statistical Learning via Mixture Models
Geoffrey McLachlan, The University of Queensland
8:35 AM
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Regression-Enhanced Random Forests
Haozhe Zhang, Iowa State University; Dan Nettleton, Iowa State University; Zhengyuan Zhu, Iowa State University
8:45 AM
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Causal Inference in a Big Data World - The Roadmap
Laura B Balzer, Harvard T.H. Chan School of Public Health
9:05 AM
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Bernstein and Hoeffding Type Inequalities for Regenerative Markov Chains
Gabriela Cio?ek, Telecom ParisTech; Patrice Bertail, Université Paris Ouest Nanterre
9:05 AM
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Hierarchical Latent Factor Models for Improving the Prediction of Surgical Complications Across Hospitals
Elizabeth Lorenzi, Duke University; Katherine Heller, Duke University; Ricardo Henao, Duke University; Zhifei Sun, Duke University
9:35 AM
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Assessing the Informational Content of Seasonality Tests by Random Forests of Conditional Inference Trees
Daniel Ollech, Deutsche Bundesbank; Karsten Webel, Deutsche Bundesbank
9:35 AM
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Group Fused Multinomial Regression
Brad Price, West Virginia University; Adam Rothman, University of Minnesota; Charles Geyer, University of Minnesota
9:45 AM
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Building Comprehensive Searches Through a Machine Learning Approach for Systematic Reviews
Corrado Lanera, University of Padova; Ileana Baldi, University of Padova; Clara Minto, University of Padova; Dario Gregori, University of Padova; Paola Berchialla, University of Torino
10:00 AM
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Sparse Concordance-Assisted Learning for Optimal Treatment Decision
Shuhan Liang, North Carolina State University; Wenbin Lu, North Carolina State University; Rui Song, NC State University; Lan Wang, University of Minnesota
10:35 AM
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Online Learning for Multi-Class Classification with Applications to Communication Network Traffic Management
Henry Lu, National Chiao Tung University
10:50 AM
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Eye-Tracking in Practice: A First Analysis of a Study on Human Postures
Jurgen Symanzik, Utah State University; Chunyang Li; Boyu Zhang, Utah State University; Breanna Studenka, Utah State University; Eric McKinney, Utah State University
10:50 AM
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New Machine Learning Tools for Discovering and Utilizing Biomarkers in Precision Medicine
Daniel Luckett, University of North Carolina at Chapel Hill; Eric Laber, North Carolina State University; Michael R Kosorok, University of North Carolina at Chapel Hill
10:55 AM
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Machine Learning Methods in the Statistical Prediction of Health Outcomes
William Padula, Johns Hopkins Bloomberg SPH
10:55 AM
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A Comparison of Risk Adjustment Models Based on Traditional Statistical and Machine Learning Techniques
Hong Kan; Hsien-Yen Chang, Johns Hopkins Bloomberg School of Public Health; Hadi Kharrazi, Johns Hopkins Bloomberg School of Public Health
11:15 AM
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Regret Bounds for Adaptive Control of Linear Quadratic Systems
Mohamad Kazem Shirani Faradonbeh, University of Michigan; Ambuj Tewari, University of Michigan; George Michailidis, University of Florida
11:25 AM
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Learning from Multiple Views of a Single Set of Observations
Daniela Witten, University of Washington
11:25 AM
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Multivariate Stochastic Process Models for Correlated Responses of Mixed Type
Tony Pourmohamad, Genentech; Herbert Lee, University of California, Santa Cruz
11:50 AM
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Improved Strongly Adaptive Online Learning Using Coin Betting
Rebecca Willett, University of Wisconsin-Madison; Kwang-Sung Jun, University of Wisconsin-Madison; Francesco Orabona, Stony Brook University; Stephen Wright, University of Wisconsin-Madison
11:50 AM
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Sequential learning of deformation models in additive manufacturing through calibration of simulation models
Tirthankar Dasgupta, Rutgers University; Ying Hung
11:50 AM
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One-Versus Two-Step Approaches to Survey Nonresponse Adjustments
Robert Fay, Westat; Minsun Riddles, Westat
2:20 PM
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High-Dimensional Precision Medicine from Patient Derived Xenograft Data
Naim Rashid, University of North Carolina at Chapel Hill; Jingxiang Chen, University of North Carolina at Chapel Hill; Michael Lawson, University of North Carolina at Chapel Hill; Daniel Luckett, University of North Carolina at Chapel Hill; Longshaokan Wang, North Carolina State University; Eric Laber, North Carolina State University; Yufeng Liu, University of North Carolina; Jen Jen Yeh, University of North Carolina at Chapel Hill; Donglin Zeng, University of North Carolina; Michael R Kosorok, University of North Carolina at Chapel Hill
2:35 PM
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Manny Parzen and Nonparametric Data Science
Subhadeep Mukhopadhyay, Temple University
2:55 PM
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Thursday, 08/03/2017
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Latent Class Analysis for Modeling and Promoting Online Learning
Jeff Douglas; Shiyu Wang, University of Georgia; Steven Culpepper, University of Illinois
8:35 AM
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Statistial Learning in Gender Classification for Facial Images
Cuixian Chen, University of North Carolina, Wilmington; Yishi Wang, University of North Carolina Wilmington
9:20 AM
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A Data Science Approach to Analyzing Neural Data
Ethan Meyers
9:50 AM
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Comparison and validation of statistical methods for predicting tree failure during storm
Elnaz Kabir; Seth Guikema, University of Michigan
10:05 AM
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Learning Curve Estimation in Medical Devices and Procedures: Hierarchical Modeling
Usha Govindarajulu, SUNY Downstate; Michael Matheny, Vanderbilt University; David Goldfarb, Montefiore Medical Center; Marco Stillo, SUNY Downstate Medical Center; Frederic Resnic, Lahey Clinic
10:05 AM
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Using Passive Data Collection, System-to-System Data Collection, and Machine Learning to Improve Economic Surveys
Brian Arthur Dumbacher, U.S. Census Bureau; Demetria Hanna, U.S. Census Bureau
10:35 AM
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What Is the the Best and Safest for Me? Data Science Methods Applied to Medical Products and Treatments
Carolyn Carroll, Stat Tech, Inc.
10:35 AM
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Evaluation of Medical Care Event Reporting in a National Household Survey
Jerrod Anderson, AHRQ; Emily Mitchell, Agency for Healthcare Research and Quality; Adam Biener, Agency for Healthcare Research and Quality
10:35 AM
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Leveraging Flexible Modeling Techniques in Data-driven Analytics
Liangyuan Hu, Icahn School of Medicine at Mount Sinai ; Madhu Mazumdar, Icahn School of Medicine at Mount Sinai
10:35 AM
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Two Trends in Solutions to Computation-Intensive Methods: Laptop vs. Graphics Processing Unit (GPU)
Junshui Ma, Merck & Co., Inc.; Vladimir Svetnik, Merck & Co., Inc.
10:55 AM
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Residuals and Influence in Bayesian Ensemble Models
Robert McCulloch, Arizona State University; Matthew Pratola, The Ohio State University
11:00 AM
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Inference and Analysis on Social Networks from Newswire Content
William Campbell, MIT Lincoln Laboratory; Lin Li, MIT Lincoln Laboratory; Joel Acevedo-Aviles, MIT Lincoln Laboratory
11:05 AM
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Leveraging Machine Learning in the Analysis of Safety Data in Drug Research and Healthcare Informatics
Melvin Munsaka, Safety Statistics and Observational Res Analytics, Takeda
11:15 AM
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Optimizing Patient Selection for Chemoprevention Through Predictive Modeling
Xi Kathy K Zhou, Weill Cornell Medical College
11:50 AM
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