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Computational Statistics

Data Science Technologies

Data Visualization

Education

Machine Learning

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Wednesday, May 29

PS01 - Opening Mixer & E-Posters
E-Poster

Wed, May 29, 5:30 PM - 7:00 PM
Grand Ballroom Foyer

Spatial Statistics and Visualization of Public Health Outcomes
Presentation Weichuan Dong, Kent State University

Teaching the ASA Guidelines in a Cross-Cultural Setting
Jing Cao, Southern Methodist University

The Daily Question: Building Student Trust and Interest in Undergraduate Introductory Probability and Statistics Courses
Presentation Matthew A. Hawks, US Naval Academy

Extending the Grammar of Graphics beyond ggplot2
Silas Bergen, Winona State University

Using Data Science to Support Enrollment Decisions in Higher Education
Monica M King, Drexel University

Data-Driven College Admissions: Useful Metrics or Numeric Nonsense?
Emily Rose Flanagan, University of Washington

Using Data Verbs to Teach the Management of Tabular Data
Chris John Malone, Winona State University

A Shiny Application to Teach the Multiple Linear Regression Analysis in a Undergraduate Course
Presentation Carlos M. Lopera-Gómez, Universidad Nacional de Colombia

Predicting Matriculation Rates of Dual Enrollment High School Students
Presentation Benjamin Kenneth Brown, Oregon Institute of Technology

A Meta-analysis on the Effect of Information and Communication Technology Tools in Second Language Acquisition
Presentation Songtao Wang, University of Victoria

Building Statistical Understanding to Support Organizational Data Culture
Karin Neff, BSD7

Thursday, May 30

CS04 - Recent Developments in Lower Rank Learning for Complex Data
Invited

Thu, May 30, 10:30 AM - 12:05 PM
Grand Ballroom K

Organizer(s): Xiao-Li Meng, Harvard University

Chair(s): Raymond Wong, Texas A&M University

10:35 AM

MCMC for Dempster-Shafer Statistical Inference
Ruobin Gong, Rutgers University

11:05 AM

Bayesian Analysis of the Covariance Matrix of a Multivariate Normal Distribution with a New Class of Priors
Dongchu Sun, University of Missouri

11:35 AM

Deep Fiducial Inference
Presentation Jan Hannig, The University of North Carolina at Chapel Hill

CS13 - Computationally Intensive Methods: Resampling and MCMC
Contributed

Thu, May 30, 1:30 PM - 3:05 PM
Grand Ballroom K

Chair(s): Honglang Wang, Indiana University-Purdue University Indianapolis

1:35 PM

Jackknife Empirical Likelihood Approach for K-Sample Tests via Energy Distance
Yongli Sang, University of Louisiana at Lafayette

1:50 PM

Gelman-Rubin: Improved Stability and a Principled Threshold
Presentation Christina Phan Knudson, University of St. Thomas

2:05 PM

Error Estimation for Randomized Numerical Linear Algebra via the Bootstrap
Miles Lopes, UC Davis

2:20 PM

A Scalable Regression Estimation Procedure for Competing Risks Data
Eric S. Kawaguchi, University of California, Los Angeles

2:35 PM

Floor Discussion

CS16 - Recent Advances in Matrix and Tensor Factorization Models
Invited

Thu, May 30, 4:00 PM - 5:35 PM
Grand Ballroom K

Organizer(s): Raymond Wong, Texas A&M University

Chair(s): Jan Hannig, The University of North Carolina at Chapel Hill

4:35 PM

Linked Matrix Factorization
Eric F. Lock, University of Minnesota

5:05 PM

Boosted Sparse and Low-Rank Tensor Regression
Kun Chen, University of Connecticut

Friday, May 31

CS23 - Advances in Analysis and Computing in Complex Data
Invited

Fri, May 31, 10:30 AM - 12:05 PM
Grand Ballroom K

Organizer(s): George Michailidis, University of Florida

Chair(s): Regina Liu, Rutgers University

10:35 AM

Graph-Based Change-Point Detection
Lynna Chu, UC Davis

11:05 AM

A Double Core Tensor Factorization and Its Applications to Heterogeneous Data
George Michailidis, University of Florida

11:35 AM

Individualized Fusion Learning (IFusion) with Applications to Personalized Inference
Minge Xie, Rutgers University

CS32 - Statistical Methods for Analyzing Large Scale or Massive Data
Contributed

Fri, May 31, 1:30 PM - 3:05 PM
Grand Ballroom K

Chair(s): Alona Kryshchenko, California State University Cannel Islands

1:35 PM

High-Dimensional Association Detection in Large Scale Genomic Studies
Hillary Koch, Pennsylvania State University

1:50 PM

Threshold Knot Selection for Large-Scale Spatial Models with Applications to the Deepwater Horizon Disaster
Casey Jelsema, West Virginia University

2:05 PM

Goodness-of-Fit Tests for Large Data Sets
Taras Lazariv, TU Dresden

2:20 PM

Big Data and Portfolio Optimization
QIYU WANG, Zhejiang Univ of Finance and Econ

2:35 PM

An Application of Linear Programming to Computational Statistics
Presentation John M. Ennis, Aigora

2:50 PM

Accelerate Pseudo-Proximal Map Algorithm and Its Application to Network Analysis
Dao Nguyen, University of Mississippi

CS34 - Computational Statistics for Large-Scale Biological Data
Invited

Fri, May 31, 3:40 PM - 5:15 PM
Grand Ballroom K

Organizer(s): Jacob Bien, University of Southern California

Chair(s): Kean Ming Tan, University of Minnesota

3:45 PM

Computationally Efficient High-Dimensional Interaction Modeling
Guo Yu, University of Washington

4:15 PM

Inference for Diversity Under Networked Models
Bryan Martin, University of Washington

4:45 PM

Variance Component Testing and Selection for a Longitudinal Microbiome Study
Jin Zhou, University of Arizona

CS45 - Change Point Detection
Contributed

Fri, May 31, 5:20 PM - 6:25 PM
Grand Ballroom K

Chair(s): Dao Nguyen, University of Mississippi

5:25 PM

Detection of Structural Changes in Correctly Specified and Misspecified Conditional Quantile Polynomial Distributed Lag (QPDL) Model Using Change-Point Analysis
Presentation KWADWO AGYEI NYANTAKYI, GHANA INSTITUTE OF MANAGEMENT AND PUBLIC ADMINISTRATION

5:40 PM

Robust Graph Change-Point Detection for Brain Evolvement Study
Honglang Wang, Indiana University-Purdue University Indianapolis

5:55 PM

Graph Theoretic Statistics for Change Detection and Localization in Multivariate Data
Presentation Matthew A. Hawks, US Naval Academy

6:10 PM

Floor Discussion

Saturday, June 1

PS06 - Computational Statistics E-Posters
E-Poster

Sat, Jun 1, 9:30 AM - 10:30 AM
Grand Ballroom Foyer

Application of Dynamic Bi-Partite Stochastic Block Models
Neil Hwang, CUNY-Bronx Community College

Estimation of Semiparametric Functional Coefficients Panel Data Model
Shaymal C Halder, Auburn University

Discovery of Gene Regulatory Networks Using Adaptively Selected Gene Perturbation Experiments
Michele Zemplenyi, Harvard University

A Computational Approach to the Structure of Subtraction Games
Kali Lacy, Purdue University

Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems
Presentation Debmalya Nandy, Penn State University

A Data-Adaptive Targeted Learning Approach of Evaluating Viscoelastic Assay Driven Trauma Treatment Protocols
Linqing Wei, UC Berkeley, Department of Biostatistics

Approximate Fiducial Computation and Deep Fiducial Inference
Presentation Gang Li, The University of North Carolina at Chapel Hill

Innovative Robust Boosting Algorithms
Presentation Zhu Wang, UT Health San Antonio

A Model Based Data Fusion Algorithm using Bayesian Hierarchal Modeling for Density Estimation of Rare Species
Purna Gamage, Wake Forest University

Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering
Israel A Almodovar-Rivera, University of Puerto Rico-Medical Science Campus

Developing Nonlinear Genetic Signatures for Enzalutamide Resistance in Prostate Cancer
Isaac Zhao, Brown University

Approximate Bayesian Computational Statistical Methods to Estimate the Strength of Divergent Selection in Yeast
Martyna Lukaszewicz, University of Idaho

Wavelet Shrinkage Using Bayesian False Discovery Rate Methods: a Comparison Study
Presentation Rodney Vasconcelos Fonseca, Unicamp

Analyzing Air Traffic Data with Spark-GraphX
Chathurangi Heshani Pathiravasan, Southern Illinois University, Carbondale

CS49 - Computational Efficiency vs. Statistical Guarantee
Invited

Sat, Jun 1, 10:00 AM - 11:35 AM
Grand Ballroom J

Organizer(s): Helen Zhang, University of Arizona

Chair(s): Helen Zhang, University of Arizona

10:05 AM

Embedding Learning
Xiaotong Shen, University of Minnesota

10:35 AM

Penalty Method for Variance Component Selection
Hua Zhou, UCLA

11:05 AM

Distributed Computing for Large Heteroskedastic Spatial Data
Zhengyuan Zhu, Iowa State University

CS54 - The IMS Program on Self-Consistency: a Fundamental Statistical Principle for Deriving Computational Algorithims
Invited

Sat, Jun 1, 1:00 PM - 2:35 PM
Grand Ballroom J

Organizer(s): Thomas Lee, UC Davis

Chair(s): Thomas Lee, UC Davis

1:05 PM

Likelihood-Free EM: Self-Consistency for Incomplete or Irregular-Pattern Data
Presentation Xiao-Li Meng, Harvard University

1:35 PM

Latent Variable Models, Self-Consistency, and Stochastic Approximation
Zhiqiang Tan, Rutgers University

2:05 PM

Self-Consistency as a Method to Develop Computationally Effective Algorithms for High-Dimensional Models
Presentation Alex Tsodikov, University of Michigan

CS61 - Advances in Regression and Modeling
Contributed

Sat, Jun 1, 2:45 PM - 3:50 PM
Grand Ballroom J

Chair(s): Yongli Sang, University of Louisiana at Lafayette

2:50 PM

Nonparametric Estimation of a Mixing Distribution for Pharmacokinetic Stochastic Models
Alona Kryshchenko, California State University Cannel Islands

3:20 PM

Floor Discussion

Online Program

Viewing Track 'Computational Statistics' only

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