Keyword Search
Sessions Were Renumbered as of May 19.
Legend:
CC-W = McCormick Place Convention Center, West Building, CC-N = McCormick Place Convention Center, North Building
H = Hilton Chicago, UC= Conference Chicago at University Center
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: learning returned 158 record(s)
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Sunday, 07/31/2016
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Fighting Fraud with Statistics!
Alyssa Frazee, Stripe
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From Statistical Visual Modeling and Computing to Communicative Learning
Tianfu Wu, University of California at Los Angeles
2:05 PM
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Two Case Studies of Statistical Approaches That Simplify the VHA Learning Health Care System
Rebecca B. McNeil, Durham VA Medical Center; Kellie J. Sims, Durham VA Medical Center; Leah L. Zullig, Durham VA Medical Center; George L. Jackson, Durham VA Medical Center; Dawn T. Provenzale, Durham VA Medical Center
2:05 PM
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Assessing Genomic Risk for Learning Problems with Neuroimaging Data
Heping Zhang, Yale School of Public Health; Chintan Mehta, Yale University
2:05 PM
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A Class of Bayesian Multivariate Time Series Models for Counts
Refik Soyer, The George Washington University; Tevfik Aktekin, University of New Hampshire; Nicholas Polson, The University of Chicago
2:05 PM
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The PICASSO Package for High Dimensions Nonconvex Sparse Learning in R
Xingguo Li; Tuo Zhao, The Johns Hopkins University; Tong Zhang, Rutgers University; Han Liu, Princeton
2:25 PM
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Surrogate-Guided Sampling Designs for Biomedical Natural Language Processing with Rare Outcomes
Wei Ling (Katherine) Katherine Tan, University of Washington; Patrick Heagerty, University of Washington
2:35 PM
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Microbial DNA for Forensic Identification and Environmental Source Tracking
Dan Knights, University of Minnesota
2:45 PM
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A Hybrid Machine-Learning Approach for DNA Mixture Interpretation
Michael Marciano, Syracuse University; Jonathan Adelman, Syracuse University
3:05 PM
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Joint Analysis of Brain Imaging Data and Genetics Data
Wenxuan Zhong, University of Georgia
3:20 PM
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Co-Clustering of Nonsmooth Graphons
David Sungjun Choi, Carnegie Mellon University
3:20 PM
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Flipping an Introduction to Applied Statistics Course for Mathematics Teacher Candidates
Ananda Jayawardhana, Pittsburg State University
4:05 PM
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Some Observations of Students' Performance and Attitudes Toward a Flipped Classroom for Introductory Statistics
Carl Lee, Central Michigan University
4:20 PM
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Learning Large-Scale DAG Models Using Overdispersion
Gunwoong Park, University of Wisconsin - Madison
4:20 PM
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An Exposition on the Propriety of Restricted Boltzmann Machines
Andrea Kaplan, Iowa State University; Daniel Nordman, Iowa State University; Stephen Vardeman, Iowa State University
4:35 PM
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Restructuring the Introductory Statistics Course to Free Class Time for Exploration and Deeper Understanding
Bonnie Moon, Brigham Young University; Craig Johnson, Brigham Young University; Ryan Cromar, Brigham Young University
4:35 PM
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An Autologistic Regression Model for Binary Classification of Hyperspectral Remote Sensing Imagery
Charmaine Dean, University of Western Ontario; Mark Wolters, Fudan University
4:55 PM
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Mary Worth Teaches Statistics via Scripting
James J. Cochran, University of Alabama
5:35 PM
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Monday, 08/01/2016
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What Can Statistics Learn from Machine Learning? And Vice Versa?
Edward Henry Kennedy, Carnegie Mellon University; Ryan Tibshirani, Carnegie Mellon University
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Sufficient Markov Decision Processes
Longshaokan Wang, North Carolina State University
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Biostatistics-Quality Improvement Collaboration Supporting a Learning Health Care System
Henry Domenico, Vanderbilt University School of Medicine
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Accelerometer Wear and Non-Wear Classification Using an Ensemble of Unsupervised Predictors
Madalina Fiterau Brostean, Stanford University; Manisha Desai, Stanford University; Jennifer Hicks, Stanford University; Thomas Robinson, Stanford University
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Developing Tools for Text Analysis of Survey Data
Randall Powers, Bureau of Labor Statistics; Brandon Kopp, Bureau of Labor Statistics; Wendy Martinez, Bureau of Labor Statistics
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Predictive Models in Horticulture: A Case Study with Royal Gala Apples
Tom M. Logan, University of Michigan; Stella McLeod, Mr. Apple New Zealand; Seth Guikema, University of Michigan
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On the Convergence Rates of Expected Improvement Methods
llya O. Ryzhov, University of Maryland
8:35 AM
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An Online Prediction Framework of Influential Users During Urgent Events on Twitter
Hechao Sun
8:50 AM
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Dispersion Modeling with an Ensemble of Trees
Hugh Chipman, Acadia University; Matthew Pratola, The Ohio State University; Robert McCulloch, The University of Chicago; Edward I. George, The Wharton School
9:00 AM
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A Complete Characterization of Graphical Probability Distributions
Kayvan Sadeghi, University of Cambridge
9:00 AM
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Learning Network Dynamics via Regularized Tensor Decomposition
Yun-Jhong Wu, University of Michigan; Elizaveta Levina, University of Michigan; Ji Zhu, University of Michigan
9:20 AM
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Deep Learning for Emulation in Uncertainty Quantification
Jared D. Huling, University of Wisconsin - Madison; Peter Qian, University of Wisconsin - Madison
9:50 AM
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E-Learning Data Analysis for Building a Personalized Recommendation System
Shuang Liu; K.F. LAM, The University of Hong Kong
9:50 AM
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Predictive Models in Horticulture: A Case Study with Royal Gala Apples
Tom M. Logan, University of Michigan; Stella McLeod, Mr. Apple New Zealand; Seth Guikema, University of Michigan
9:50 AM
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List-Based Interpretable Dynamic Treatment Regimes
Yichi Zhang, North Carolina State University; Eric Laber, North Carolina State University; Anastasios Tsiatis, North Carolina State University; Marie Davidian, North Carolina State University
10:35 AM
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The Results of Blended Instruction in Quantitative Methods in Public Health: A Pilot Study
Adam Sullivan, Brown University; Marcello Pagano, Harvard
10:35 AM
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Incorporating Service Learning into an Undergraduate Statistical Consulting Course
Samantha Bates Prins, James Madison University
10:35 AM
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Personalized Dose Finding Using Outcome Weighted Learning
Guanhua Chen, Vanderbilt University ; Donglin Zeng, The University of North Carolina at Chapel Hill; Michael R. Kosorok, The University of North Carolina at Chapel Hill
10:35 AM
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Developing Tools for Text Analysis of Survey Data
Randall Powers, Bureau of Labor Statistics; Brandon Kopp, Bureau of Labor Statistics; Wendy Martinez, Bureau of Labor Statistics
10:55 AM
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Online Introductory Biostatistics for Graduate Students: Successes and Failures Teaching a Diverse Student Body
Rebecca Andridge, The Ohio State University
10:55 AM
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Machine-Learning Tools for Finding Biomarkers in Precision Medicine
Jonathan Hibbard, The University of North Carolina at Chapel Hill; Michael R. Kosorok, The University of North Carolina at Chapel Hill
11:00 AM
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Enabling Privacy Preserving Machine Learning at Scale
Farinaz Koushanfar, UCSD
11:00 AM
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Measured Community Engagement Outcomes Increases in a Business Statistics Class
Amy Phelps, Duquesne University
11:05 AM
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Manifold Data Analysis
Hyun Bin Kang; Matthew Reimherr, Penn State University
11:05 AM
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The Evaluation of a Pedagogical Tool for Quantitative Literacy
Gerald Iacullo, Berkeley College
11:10 AM
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Teaching Biostatistical Literacy: A Flipped-Classroom Approach
Ann M. Brearley, University of Minnesota School of Public Health
11:15 AM
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Nonparametric Distributed Learning Architecture: Algorithm and Application
Scott Bruce, Temple University; Zeda Li, Temple University; Hsiang-Chieh Yang, Temple University; Subhadeep Mukhopadhyay, Temple University Fox School of Business
11:20 AM
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Online Revenue Management Using Thompson Sampling
Kris Ferreira, Harvard Business School; He Wang, MIT Operations Research Center; David Simchi-Levi, MIT Operations Research Center
11:35 AM
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A General Framework for Bayes Structured Linear Models
Harrison Zhou, Yale University; Chao Gao, Yale University
11:50 AM
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Flexible Functional Regression Methods for Estimating Individualized Treatment Regimes
Adam Ciarleglio, Columbia University; Eva Petkova, New York University; Thaddeus Tarpey, Wright State University; Robert Todd Ogden, Columbia University
12:05 PM
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Manifold Learning: Dimension Reduction Versus Parameterization Recovery
Michael Trosset, Indiana University; Lijiang Guo, Indiana University
12:05 PM
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Overcoming Computational Challenges of Subgroup Identification Using SIDES Method
Ilya Lipkovich, Quintiles; Alex Dmitrienko, Quintiles
2:05 PM
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Nonparametric Methods for Doubly Robust Estimation of Continuous Treatment Effects
Edward Kennedy, University of Pennsylvania; Zongming Ma, University of Pennsylvania; Dylan Small, University of Pennsylvania
2:05 PM
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Benchmarking and Assessment for Multiple Imputation
Gerko Vink, Utrecht University
2:05 PM
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Motivated Student Engagement in an Online Biostatistics Course
Wei Zhuang, Creighton University
2:05 PM
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Bayesian Statistics and Information Theory
Jose Guardiola, Texas A&M University - Corpus Christi
2:35 PM
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Large-Margin Classification with Multiple Decision Rules
Patrick Kimes, Roche Sequencing; Yufeng Liu, The University of North Carolina at Chapel Hill; J. S. Marron, The University of North Carolina at Chapel Hill; David Neil Hayes, The University of North Carolina at Chapel Hill
2:45 PM
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Learning with Differential Privacy: Stability, Learnability, and the Sufficiency and Necessity of ERM Principle
Yu-Xiang Wang, Carnegie Mellon University; Jing Lei, Carnegie Mellon University; Stephen E. Fienberg, Carnegie Mellon University
2:45 PM
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Bayesian Nonparametric Methods for Precision Medicine
Qian Guan, North Carolina State University; Eric Laber, North Carolina State University; Dipankar Bandyopadhyay, Virginia Commonwealth University; Brian J. Reich, North Carolina State University
2:55 PM
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Applications of Machine Learning in Environmetrics: Detecting Dynamic Trend-Based Clusters
Xin Huang, The University of Texas at Dallas; Iliyan R. Iliev, The University of Texas at Dallas; Lyubchich Vyacheslav, University of Maryland Center for Environmental Science; Alexander Brenning , University of Jena; Yulia R. Gel, The University of Texas at Dallas
3:35 PM
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An Integrative Classification Model for Multiple Sclerosis Lesion Detection in Multimodal MRI
Fengqing Zhang, Drexel University; Wenxin Jiang, Northwestern University; Ji-Ping Wang, Northwestern University
3:35 PM
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Localized Semiparametric Prediction: A Precision Medicine Approach in a Trauma Patient Population
Sara E. Moore, University of California at Berkeley; Alan E. Hubbard, University of California at Berkeley; Mitchell J. Cohen, University of California at San Francisco
3:35 PM
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Tuesday, 08/02/2016
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Machine Learning Applications for Survey Design, Collection, and Adjustment: Going Beyond the Trees to See Clusters, Forests, and Neighbors
Trent Buskirk, Marketing Systems Group
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ZIP Codes and Neural Networks: Machine Learning for Handwritten Number Recognition
Cuixian Chen, The University of North Carolina at Wilmington; Taylor Harbold, The University of North Carolina at Wilmington; Courtney Rasmussen, The University of North Carolina at Wilmington; Michelle Page, The University of North Carolina at Wilmington
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Machine Learning for Exploratory Analyses of Psychological Data
Gitta Lubke
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Employing Machine Learning Approaches in Social Scientific Analyses
Arne Bethmann, Institute for Employment Research; Jonas Beste, Institute for Employment Research
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Improved Disease Burden Modeling from Administrative Health Care Data
Ralph (PhD Student) Ward , Medical University of South Carolina; Mulugeta Gebregziabher, Medical University of South Carolina; Leonard Egede, Health Equity and Rural Outreach Innovation Center; Lewis Frey, Medical University of South Carolina; Viswanathan Ramakrishnan, Medical University of South Carolina; Robert Axon, Medical University of South Carolina
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Learning About Mechanisms: Causal Mediation Analysis Using R
Teppei Yamamoto, MIT
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Predicting Binary Outcome with Unequal Misclassification Cost
Shuchismita Sarkar, University of Alabama; Michael D. Porter, University of Alabama
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Learning Health Systems: From Ideas to Reality
Rebecca Yates Coley, Johns Hopkins Bloomberg School of Public Health
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Modeling Heterogeneity in Motor Learning Using Heteroskedastic Functional Principal Components
Daniel Backenroth, Columbia Mailman School of Public Health; Jeff Goldsmith, Columbia Mailman School of Public Health; Tomoko Kitago, Columbia University Medical Center; John Krakauer, Johns Hopkins School of Medicine
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Learning Parameter Heterogeneity in Data Integration
Lu Tang, University of Michigan; Peter X. K. Song, University of Michigan
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The Knockoff Filter for FDR Control in Group-Sparse and Multitask Regression
Ran Dai, The University of Chicago; Rina Foygel Barber, The University of Chicago
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Postoperative Neonatal Mortality Prediction Using Superlearning
Jennifer N. Cooper, Nationwide Children's Hospital Research Institute; Katherine J. Deans, Nationwide Children's Hospital Research Institute; Peter C. Minneci, Nationwide Children's Hospital Research Institute
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Statistical Learning Methods for Record Linkage: A Pioneer Mortality Example
Kristina Murri, Brigham Young University
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Developing an Index-Based Methodology to Forecast the Integrated Risk of Extreme Weather to Agricultural Production Systems
Nathaniel Kenneth Newlands, Agriculture and Agri-Food Canada
8:35 AM
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Imputing Data That Are Missing at High Rates Using a Boosting Algorithm
Katherine Cauthen, Sandia National Laboratories; Gregory Lambert, Sandia National Laboratories; Jaideep Ray, Sandia National Laboratories; Sophia Lefantzi, Sandia National Laboratories
8:35 AM
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Unsupervised Anomaly Detection in Time Series with Application in Electricity Demand Forecasting
Bei Chen, IBM Research; Mathieu Sinn, IBM Research; Ulrike Fischer , IBM Research
8:55 AM
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Addressing Challenges to Implementing Active Learning for All Sections of Introductory Statistics at a Large University
Ginger Rowell, Middle Tennessee State University; Lisa Holmes Green, Middle Tennessee State University; Nancy Holmes McCormick, Middle Tennessee State University; Scott Holmes McDaniel, Middle Tennessee State University; Jeremy Holmes Strayer, Middle Tennessee State University
9:05 AM
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Predicting Chemical Dose-Response Toxicity Through Chemical Structure Activity Relationships
Matthew Wheeler, CDC/NIOSH
9:15 AM
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Predictive Modeling of Severity of Injuries in Motor Vehicle Crashes
Aditi Pradeep Sharma, University of Maryland Baltimore County; Michael Wierzbicki, The EMMES Corporation; Gaurav Sharma, The EMMES Corporation
9:15 AM
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Stabilized Dynamic Treatment Regimes
Yingqi Zhao, Fred Hutchinson Cancer Research Center; Ruoqing Zhu, University of Illinois at Urbana-Champaign; Guanhua Chen, Vanderbilt University
9:25 AM
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Predictive Modeling of Inpatient Fall of Stroke Patients Using electronic medical records data
Yin Liu, Princeton Pharmatech; Cindy Jin, Lawrenceville School; Jeffrey Yangang Zhang, Princeton Pharmatech
9:50 AM
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Learning the Structure of Biological Networks
Richard Bonneau, New York University; Christian Müller, Simons Foundation
9:55 AM
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Postoperative Neonatal Mortality Prediction Using Superlearning
Jennifer N. Cooper, Nationwide Children's Hospital Research Institute; Katherine J. Deans, Nationwide Children's Hospital Research Institute; Peter C. Minneci, Nationwide Children's Hospital Research Institute
10:00 AM
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Communication Over a Noisy Channel Using High-Dimensional Linear Regression with Gaussian Design
Cynthia Rush, Yale University; Adam Greig, University of Cambridge; Ramji Venkataramanan, University of Cambridge
10:05 AM
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Data-Driven Dynamical Systems Models for the Management of Diabetes Through Mobile Interventions
Daniel J. Luckett, The University of North Carolina at Chapel Hill; Eric Laber, North Carolina State University; Michael R. Kosorok, The University of North Carolina at Chapel Hill
10:35 AM
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Decoding Brain States from fMRI Data with a Machine Learning Method
Elizabeth Chou
10:35 AM
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Learning Parameter Heterogeneity in Data Integration
Lu Tang, University of Michigan; Peter X. K. Song, University of Michigan
10:40 AM
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Computationally Efficient Question Selection in Adaptive Questionnaires
John Riddles, George Mason University; James E. Gentle, George Mason University
10:50 AM
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Modeling Heterogeneity in Motor Learning Using Heteroskedastic Functional Principal Components
Daniel Backenroth, Columbia Mailman School of Public Health; Jeff Goldsmith, Columbia Mailman School of Public Health; Tomoko Kitago, Columbia University Medical Center; John Krakauer, Johns Hopkins School of Medicine
10:55 AM
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Machine Learning Methods in High-Dimensional Branching Processes
Anand N. Vidyashankar, George Mason University
10:55 AM
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Statistics in Personalized Medicine
Mark van der Laan, University of California at Berkeley; Alexander Luedtke, University of California at Berkeley
11:00 AM
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Learning Communities: An Emerging Platform for Research in Statistics
Mark Daniel Ward, Purdue University
11:00 AM
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Statistical Learning Methods for Record Linkage: A Pioneer Mortality Example
Kristina Murri, Brigham Young University
11:05 AM
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Using Machine Learning to Correct for Survey Nonresponse Bias
Curtis Signorino, University of Rochester; Antje Kirchner, University of Nebraska - Lincoln
11:15 AM
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Generalized Fiducial Inference for Massive Heterogeneous Data
Jan Hannig, The University of North Carolina at Chapel Hill
11:25 AM
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The ASA DataFest: Learning by Doing
Robert Gould, University of California at Los Angeles
11:25 AM
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Matchmaker, Data Scientist, or Both? Using Unsupervised Learning Methods for Matching Nonprobability Samples to Probability Sample
Trent Buskirk, Marketing Systems Group; David Dutwin, SSRS
11:35 AM
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Methodological Strategies to Define a Generalizable Model for Machine Learning Ensemble Techniques
Joel Correa da Rosa, Rockefeller University; Lewis Tomalin, Icahn School of Medicine at Mount Sinai; Mayte Suárez-Fariñas, Icahn School of Medicine at Mount Sinai
11:35 AM
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Fusion Learning from Complex Data Sets to Efficient Goal-Directed Individualized Inference
Regina Liu, Rutgers University; Minge Xie, Rutgers University
11:50 AM
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The Knockoff Filter for FDR Control in Group-Sparse and Multitask Regression
Ran Dai, The University of Chicago; Rina Foygel Barber, The University of Chicago
11:50 AM
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Maximizing Text Mining Performance: The Impact of Pre-Processing
Dario Gregori, University of Padova; Paola Berchialla, University of Torino; Nicola Soriani, University of Padova; Ileana Baldi, University of Padova; Corrado Lanera, University of Padova
11:55 AM
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A Case Study in Machine Learning Approaches to Survey Nonresponse Adjustments
Minsun Riddles, Westat; Bob Fay, Westat; David McGrath, Defense Manpower Data Center; Eric Falk, Defense Manpower Data Center
11:55 AM
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Learning High-Dimensional Discrete Multivariate Auto-Regressive Models
Garvesh Raskutti, University of Wisconsin - Madison
2:05 PM
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Traditional vs. Simulation-Based: Curricula Comparison in a Small-Scale Educational Experiment
Karsten Maurer, Miami University; Dennis Lock, Miami Dolphins
2:05 PM
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Efficient Sampling Strategy for SVM Through Semi-Supervised Active Learning
Yaru Shi, University of Illinois at Chicago; Yoonsang Kim, University of Illinois at Chicago; Ganna Kostygina, University of Illinois at Chicago; Sherry Emery, University of Illinois at Chicago
2:35 PM
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Being Bayesian in a Big Data World
David Banks, Duke University
2:55 PM
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Nonparametric Bayesian Learning of Heterogeneous Dynamic Transcription Factor Networks
Xiangyu Luo, The Chinese University of Hong Kong; Yingying Wei, The Chinese University of Hong Kong
3:05 PM
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Statistical Learning Toolbox for Prediction
Umashanger Thayasivam, Rowan University
3:20 PM
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Predicting Industry Output with Statistical Learning Methods
Peter Meyer, Bureau of Labor Statistics; Wendy Martinez, Bureau of Labor Statistics
3:35 PM
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Wednesday, 08/03/2016
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Members Choice: Hot Topics in Statistical Learning and Data Mining
Glen Wright Colopy, University of Oxford
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Segmentation Analysis in Market Research
Joseph Retzer, ACT Market Research Solutions; Ewa Nowakowska, GfK
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Predicting Patient Costs
Grace Shrader, University of Wisconsin - Madison; Jonathan Berthet, The University of Chicago; Katherine Tong, The University of Chicago; David O. Meltzer, The University of Chicago
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Learning Bayesian Update via Shiny: Understanding Bayesian Methods Through Visualization
J. Jack Lee, MD Anderson Cancer Center
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Creating a Course on Statistical Learning
Sam Behseta, California State University at Fullerton
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Properties of Adaptive Clinical Trial Signature Design in the Presence of Gene and Gene-Treatment Interaction
Alexander Cambon, University of Louisville; Shesh N. Rai, University of Louisville; Guy Brock, University of Louisville
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Time Series Matching for Novelty Detection in the Stepdown Ward: A Gaussian Process Approach
Glen Wright Colopy, University of Oxford; Marco A. F. Pimentel; Stephen J. Roberts; David A. Clifton
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Application of Computer Vision and Machine Learning to Public Health Data Validation
Daniel Robertson, CDC; Jin-Mann Lin, CDC
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Modeling Temporal Dependence to Improve Learning Algorithms for Streaming Data
Maggie Johnson, Iowa State University; Petrutza Caragea, Iowa State University; Lisa Bramer, Pacific Northwest National Laboratory; Bryan Stanfill, Pacific Northwest National Laboratory; Sarah Reehl, Pacific Northwest National Laboratory
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STAT-MAPS: A Matrix-Based Electronic Learning Tool for Beginning Statistics Students
Concetta DePaolo, Indiana State University
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Statistical Learning Guided by Managerial Decision Making
Bo Li, Tsinghua University
8:35 AM
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Detecting Real-Time Substance Use from Wearable Biosensor Data Stream
Chanpaul Jin Wang, University of Massachusetts Medical School; Hua Fang, University of Massachusetts Medical School; Stephanie Carreiro, University of Massachusetts Medical School; Honggang Wang, University of Massachusetts - Dartmouth; Edward Boyer, University of Massachusetts Medical School
8:50 AM
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Statistics and Machine Learning in Pharmacovigilance for Signal Detection of Cardiovascular Risks
James Chen, FDA/NCTR; Weizhong Zhao , FDA/NCTR; Wen Zou, FDA/NCTR
9:05 AM
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Deep Spatial Learning for Forensic Geolocation with Microbiome Data
Neal Grantham; Brian J. Reich, North Carolina State University; Eric Laber, North Carolina State University
9:20 AM
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Doubly Robust Regression Trees Under Competing Risks
Youngjoo Cho, University of Rochester Medical Center; Robert Strawderman, University of Rochester Medical Center
9:35 AM
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Learning the Underlying Social Network from Continuous-Time Pairwise Interaction Data
Wesley Lee, University of Washington; Bailey Fosdick, Colorado State University; Tyler McCormick, University of Washington
9:35 AM
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Data Normalization by Fisher-Yates Transformation
Yayan Zhang, Merck ; Javier Cabrera, Rutgers University; Birol Emir, Pfizer Inc & Columbia University
10:05 AM
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Free Lunches with Sparse Bayesian Nonparametric Learning: A Probabilistic Exploration of Lower Dimensional Structure Discovery with Sparse High-Dimensional Data
Anjishnu Banerjee, Medical College of Wisconsin
10:05 AM
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Machine Learning and Causality
Guido Imbens, Stanford University
10:35 AM
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Covariate Balancing Propensity Score via Tailored Loss Function
Qingyuan Zhao, Stanford University; Trevor Hastie, Stanford University
11:05 AM
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Sequential Monte Carlo Smoothing with Parameter Estimation
Biao Yang, The George Washington University; Jonathan Stroud, Georgetown University; Gabriel Huerta, University of New Mexico
11:05 AM
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Reduced Sample-Compressed Learning of Big Probability Distributions
Subhadeep Mukhopadhyay, Temple University Fox School of Business
11:05 AM
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On Safe Semi-Supervised Learning
Kenneth Ryan; Mark Culp, West Virginia University
11:20 AM
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Using Inverse Probability of Censoring Weighted Bagging to Adapt Machine-Learning Techniques to Censored Data
Ales Kotalik, University of Minnesota; Julian Wolfson, University of Minnesota; David Vock, University of Minnesota School of Public Health; Gediminas Adomavicius, University of Minnesota; Sunayan Bandyopadhyay, University of Minnesota
11:20 AM
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Integrated Kernel Learning for Genomic Data Mining and Prediction
Xuefeng Wang, SUNY Stony Brook; Zhenyu Zhang, SUNY Stony Brook; Minqin Chen, SUNY Stony Brook
11:25 AM
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Bayesian Neural Network for Predicting Survival Time of Competing Risks
Taysseer Sharaf, Slippery Rock University
11:35 AM
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Using Machine Learning Algorithms for Handling Missingness: Application to Predicting Drug-Disease and Drug-Drug Interactions
Ruoshui Zhai, Brown University; Roee Gutman, Brown University
11:35 AM
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Spatial-Nonspatial Multidimensional Adaptive Radiotherapy Treatment
David Vock, University of Minnesota School of Public Health; Guadalupe M. Canahuate, University of Iowa; G.Elisabeta Marai, University of Illinois at Chicago; C. David Fuller, MD Anderson Cancer Center
11:55 AM
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Propensity Score Matching Using Random Forest in Educational Data Mining Problems
Richard Levine, San Diego State University
2:05 PM
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Generalized Difference in Difference Models with Gaussian Processes
William Herlands, Carnegie Mellon University; Daniel B. Neill, Carnegie Mellon University; Akshaya Jha, Carnegie Mellon University; Seth Flaxman, University of Oxford; Kun Zhang, Carnegie Mellon University
2:35 PM
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Optimizing Dynamic Treatment Regimes via Quality-Adjusted Q-Learning and Threshold Utility Analysis for Subgroup Analysis in Clinical Trials
Geoffrey Johnson; Andrew Topp, University of Pittsburgh; Abdus S. Wahed, University of Pittsburgh
2:50 PM
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Archetypal Analysis: Three Case Studies
Anna Quach; Adele Cutler, Utah State University
3:05 PM
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Sparsity-Oriented Importance Learning
Chenglong Ye, University of Minnesota; Yi Yang, McGill University; Yuhong Yang, University of Minnesota
3:05 PM
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Learning About Nonrespondents' Characteristics Using Standard Exploratory Data Analysis (EDA) Tools
MoonJung Cho, Bureau of Labor Statistics; Larry Lang, Bureau of Labor Statistics
3:20 PM
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Collaborative Targeted Learning for Large-Scale and High-Dimensional Data
Cheng Ju, University of California at Berkeley; Mark van der Laan, University of California at Berkeley; Susan Gruber, Harvard T.H. Chan School of Public Health; Jessica Franklin, Brigham and Women's Hospital; Richard Wyss, Brigham and Women's Hospital; Wesley Eddings, Brigham and Women's Hospital; Sebastian Schneeweiss, Brigham and Women's Hospital
3:20 PM
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Estimating Individualized Treatment Rules for Ordinal Treatments
Jingxiang Chen; Yufeng Liu, The University of North Carolina at Chapel Hill; Michael R. Kosorok, The University of North Carolina at Chapel Hill; Haoda Fu, Eli Lilly and Company; Xuanyao He, Eli Lilly and Company
3:35 PM
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Efficient Discovery of Heterogeneous Treatment Effects in Randomized Experiments via Anomalous Pattern Detection
Edward McFowland, Carlson School of Management; Sriram Somanchi, University of Notre Dame; Daniel B. Neill, Carnegie Mellon University
3:35 PM
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Thursday, 08/04/2016
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Online Algorithms for Statistical Learning
Josh Day, North Carolina State University
8:35 AM
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Is Q-Learning a Valid Method of Knowing?
Francisco Diaz, University of Kansas Medical Center
8:35 AM
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Estimation of Heterogeneity for Multinomial Probit Models
Yixi Xu; Qiang Liu, Purdue University; Xiao Wang, Purdue University
8:35 AM
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Quadratically Regularized Functional Canonical Correlation Analysis and Its Application to Genetic Pleiotropic Analysis of Multiple Phenotypes
Nan Lin; Yun Zhu, Tulane University; Fen Peng, The University of Texas Health Science Center at Houston; Jinying Zhao, Tulane University; Momiao Xiong, The University of Texas Health Science Center at Houston
8:50 AM
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Comparison of Some Subgroup Identification Algorithms for Precision Medicine in Drug Development
Xin Huang; Yan Sun, AbbVie; Saptarshi Chatterjee, AbbVie; Viswanath Devanarayan, AbbVie
8:55 AM
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An Undergraduate Data Science Program
James Albert, Bowling Green State University; Maria Rizzo, Bowling Green State University
9:20 AM
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Adaptive Sequential Model Selection
William Fithian, University of California at Berkeley; Jonathan Taylor, Stanford University; Robert Tibshirani, Stanford University; Ryan Tibshirani, Carnegie Mellon University
10:35 AM
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Adaptive Control Algorithms for Managing Infectious Diseases on a Network
Nicholas Meyer, North Carolina State University; Eric Laber, North Carolina State University; Brian J. Reich, North Carolina State University; Krishna Pacifici, North Carolina State University
10:50 AM
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Multicategory Personalized Treatment Rule with Application to Diabetes Data Analysis
Xuanyao He, Eli Lilly and Company; Haoda Fu
10:55 AM
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New Machine-Learning Approaches to Causal Inference
Cynthia Rudin, Duke University
11:25 AM
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Doubly Robust Estimation of Optimal Treatment Regime in Additive Hazards Regression
Wenbin Lu, North Carolina State University; Suhyun Kang, North Carolina State University
11:50 AM
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Pathwise Coordinate Optimization for Nonconvex Sparse Learning: Algorithm and Theory
Tuo Zhao, The Johns Hopkins University; Han Liu, Princeton; Tong Zhang, Rutgers University
12:05 PM
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