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Sessions Were Renumbered as of May 19.
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H = Hilton Chicago, UC= Conference Chicago at University Center
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: Big Data returned 62 record(s)
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Sunday, 07/31/2016
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Can Early Analysis Predict Alzheimer's Trial Success?
Kun Jin, FDA/CDER
2:50 PM
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Big Data Regression and Prediction for High-Throughput Genomic Data
Weiqiang Zhou, Johns Hopkins Bloomberg School of Public Health; Ben Sherwood, Johns Hopkins Bloomberg School of Public Health; Zhicheng Ji, Johns Hopkins Bloomberg School of Public Health; Fang Du, Johns Hopkins Bloomberg School of Public Health; Jiawei Bai, Johns Hopkins Bloomberg School of Public Health; Hongkai Ji, Johns Hopkins Bloomberg School of Public Health
2:50 PM
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Thinking with Data Using R and RStudio: Powerful Idioms for Analysts
Nicholas Jon Horton, Amherst College; Randall Pruim, Calvin College; Daniel Kaplan, Macalester College
4:05 PM
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Generalized Full Matching
Fredrik Sävje, University of California at Berkeley; Michael Higgins, Kansas State University; Jasjeet Sekhon, University of California at Berkeley
4:25 PM
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A Multiresolution Model for Activation and Connectivity in fMRI Data with Functional Estimation of the Haemodynamic Response
Stefano Castruccio, Newcastle University; Hernando Ombao, University of California at Irvine; Thomas Theussl, King Abdullah University of Science and Technology; Marc Genton, KAUST
4:55 PM
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Monday, 08/01/2016
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From Statistician to Data Scientist: How to Prepare?
Ming Li, Walmart
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Where Do Marine Mammals Go? Bayesian Data Fusion Provides the Answer
Yang Seagle Liu, University of British Columbia; James V. Zidek, University of British Columbia; Brian C. Battaile, University of British Columbia; Andrew W. Trites, University of British Columbia
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Pitch Quantification in Baseball: Reducing a Pitch to a Single Number
Jason Wilson, Biola University
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Incorporating Big Data into an Introductory Statistics Course
Paul Stephenson, Grand Valley State University; Laura Kapitula, Grand Valley State University
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Social Signal Processing: Building Computational Models of Human Behavior in Digital Environments
William Rand, University of Maryland; David Darmon, Uniformed Services University of the Health Sciences; Michelle Girvan, University of Maryland
8:35 AM
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The Biglasso Package: Extending Lasso Model Fitting to Big Data in R
Yaohui Zeng, University of Iowa; Patrick Breheny, University of Iowa
8:35 AM
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Where Do Marine Mammals Go? Bayesian Data Fusion Provides the Answer
Yang Seagle Liu, University of British Columbia; James V. Zidek, University of British Columbia; Brian C. Battaile, University of British Columbia; Andrew W. Trites, University of British Columbia
9:30 AM
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Pitch Quantification in Baseball: Reducing a Pitch to a Single Number
Jason Wilson, Biola University
10:35 AM
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Incorporating Big Data into an Introductory Statistics Course
Paul Stephenson, Grand Valley State University; Laura Kapitula, Grand Valley State University
10:50 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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Correcting Biases in Auxiliary Data to Produce Better Estimates
Masahiko Aida, Civis Analytics
11:50 AM
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Convergence and Stability Properties of Variance-Function Estimators Used in the Integration of Surveys and Alternative Data Sources
John Eltinge, Bureau of Labor Statistics
12:05 PM
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Big Data Algorithms for Rank-Based Estimation
John Kapenga, Western Michigan University; John Kloke, University of Wisconsin; Joseph McKean, Western Michigan University
2:35 PM
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Optimal Reconciliation of Constrained and Unconstrained Apparel Demand Forecasts Using a Hierarchical Time Series Approach
Ginger Holt, Walmart Labs
3:05 PM
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Approximations of Markov Chains and Bayesian Inference
James Johndrow, Duke University; Jonathan Mattingly, Duke University; Sayan Mukherjee, Duke University; David Dunson, Duke University
3:05 PM
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Causal Inference from Big Data: Theoretical Foundations and the Data-Fusion Problem
Elias Bareinboim, Purdue University
3:05 PM
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Robust Bayesian Inference via the Tilted Posterior
Yixin Wang, Columbia University; David Blei, Columbia University
3:35 PM
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Tuesday, 08/02/2016
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Divide and Recombine (DandR) with Tessera: High-Performance Computing for the Analysis of Big Data and High-Complexity Analytics
Yuying Song, Purdue University; Bowei Xi, Purdue University; Ryan Hafen, Hafen Consulting; William S. Cleveland, Purdue University
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Data Science: Bridging Academia and Industry
Justin Dyer, Google; Donal McMahon, Google
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A New Distribution to Describe Big Data
Yuanyuan Zhang, University of Manchester
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A Generalized Ordered Response Model
Kramer Quist, Brigham Young University; James McDonald, Brigham Young University; Carla Johnston, University of California at Berkeley
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Statistical Challenges in Big Data Analysis of the Hotel Industry
Kai-Sheng Song , University of North Texas
8:35 AM
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How NOT to Do A/B Testing
David Charles Draper, University of California at Santa Cruz
9:25 AM
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Nonparametric Regression with Adaptive Smoothness via a Convex Hierarchical Penalty
Asad Haris, University of Washington; Ali Shojaie, University of Washington; Noah Simon, University of Washington
10:05 AM
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Model Calibration Utilizing Summary-Level Information from External Big Data
Nilanjan Chatterjee, The Johns Hopkins University; Yi-Hau Chen, Academia Sinica; Paige Maas, National Cancer Institute; Raymond Carroll, Texas A&M University
10:35 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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A Generalized Ordered Response Model
Kramer Quist, Brigham Young University; James McDonald, Brigham Young University; Carla Johnston, University of California at Berkeley
12:05 PM
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Trading Strategy Using Stock Moves Prediction and Sentiment Analysis
Brahim Brahim, Big Data Visualizations Inc.; Sun Makosso-Kallyth, McMaster University
2:20 PM
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Analysis of Methane Data Collected by Google Street View Vehicles
Zachary Weller; Jennifer Hoeting , Colorado State University; Adam Gaylord, Colorado State University; Joe von Fischer, Colorado State University
2:50 PM
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Computationally Efficient Nonparametric Testing
Guang Cheng, Purdue University; Zuofeng Shang, Binghamton University
2:55 PM
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Being Bayesian in a Big Data World
David Banks, Duke University
2:55 PM
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Big Data Methods for Scraping Government Tax Revenue from the Web
Brian Dumbacher, U.S. Census Bureau; Cavan Capps, U.S. Census Bureau
3:35 PM
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Wednesday, 08/03/2016
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A Classroom Data Analysis Project Comparing 1960s Local Radio Chart Data to the National Billboard Charts
John Gabrosek, Grand Valley State University; Len O'Kelly, Grand Valley State University
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Statistical Methods for Genomic Data Integration
Veera Baladandayuthapani, MD Anderson Cancer Center
8:35 AM
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Time Delay Boolean Networks for Big Data
Henry Lu, National Chiao Tung University
9:20 AM
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Data Science Education
Constantine Gatsonis, Brown University; Alfred Hero, University of Michigan; John Lafferty, The University of Chicago; Raghu Ramakrishnan, Microsoft
10:35 AM
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PIE: Simple, Scalable, and Accurate Posterior Interval Estimation
Cheng Li, Duke University; Sanvesh Srivastava, University of Iowa; David Dunson, Duke University
11:20 AM
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On Safe Semi-Supervised Learning
Kenneth Ryan; Mark Culp, West Virginia University
11:20 AM
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Small-Area Estimation for High-Dimensional Non-Gaussian Dependent Data
Jonathan R. Bradley, University of Missouri; Scott H. Holan, University of Missouri; Christopher Wikle, University of Missouri
11:35 AM
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Carpe Datum! Bill Cleveland's Contributions to Data Science and Big Data Analysis
Steve Scott, Google Analytics
11:35 AM
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Role of Functional Data Analysis in the Big Data Era: Applications to Precision Medicine
Hulin Wu, The University of Texas Health Science Center at Houston
11:50 AM
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Scaling Up Statistical Models to Hadoop Using Tessera
Jim Harner, West Virginia University
11:55 AM
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Cognostics: Metrics Enabling Detailed Interactive Visualization of Big Data
Barret Schloerke
2:05 PM
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Covariance-Insured Screening Methods for Ultrahigh-Dimensional Variable Selection
Yi Li, University of Michigan; Ji Zhu, University of Michigan; Jiashun Jin, Carnegie Mellon University; Kevin He, University of Michigan; Yanming Li, University of Michigan
2:30 PM
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A New Class of Measures for Independence Test with Its Application in Big Data
Qingcong Yuan, University of Kentucky; Xiangrong Yin, University of Kentucky
2:35 PM
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Subsampling for Feature Selection from Large Regression Data
Yiying Fan, Cleveland State University; Jiayang Sun, Case Western Reserve University
2:35 PM
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Epigenome Isoform Analysis with Applications
Hongkai Ji, Johns Hopkins Bloomberg School of Public Health; Weixiang Fang, Johns Hopkins Bloomberg School of Public Health
2:45 PM
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Identifying Typical Patterns and Atypical Behavior in Copious Amounts of Streaming Data
Brett Amidan, Pacific Northwest National Laboratory; James Follum, Pacific Northwest National Laboratory
2:50 PM
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Making Sense of Digital Experiments with Bayesian Nonparametrics
Matt Taddy, Chicago Booth
2:55 PM
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Thursday, 08/04/2016
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Teaching Students to Work with Big Data Through Visualizations
Shonda Kuiper, Grinnell College
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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Storage Issues and Assessment Arising from Large-Scale Simulations
Emily Casleton, Los Alamos National Laboratory; Joanne Wendelberger, Los Alamos National Laboratory; Jonathan Woodring, Los Alamos National Laboratory
9:10 AM
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Interpretable High-Dimensional Inference via Score Maximization with an Application in Neuroimaging
Simon Vandekar, University of Pennsylvania; Philip Reiss, New York University; Russell Shinohara, University of Pennsylvania
9:20 AM
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HVAR: High-Dimensional Forecasting via Interpretable Vector Autoregression
David Matteson, Cornell University; William B. Nicholson, Cornell University ; Jacob Bien, Cornell University
9:25 AM
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Differentially Private Data Synthesis Partitioning for Big Data
Claire McKay Bowen, University of Notre Dame; Fang Liu, University of Notre Dame
9:45 AM
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Big, Deep, and Dark Data: Fundamentals, Research Challenges, and Opportunities
Ivo Dinov, Statistics Online Computational Resource
10:05 AM
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Cross-Disciplinary Minor in Data Science: A New Paradigm for Partnership Across Disciplines
Andrew Schaffner, Cal Poly; Alexander Dekhtyar, Cal Poly
10:55 AM
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