Statistical Modeling for  Correlated Data

Organizer: Hyokyoung (Grace) Hong, Michigan State University
Chair: Hyokyoung (Grace) Hong, Michigan State University
Time: Saturday, 16:30–18:00
Room: LInC 368

16:30-17:00

Generalized Linear Mixed Models with Gaussian Mixture Random Effects

Yi Li, University of Michigan

17:00-17:30

USAT: A Unified Score-based Association Test for Multiple Phenotype-Genotype Analysis

Saonli Basu, University of Minnesota

17:30-18:00

Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters

Yoonkyung Lee, Ohio State University

Understanding Non-Convex Optimization Problems in Statistical Learning

Organizer: Rahul Mazumder, Massachusetts Institute of Technology
Chair: Rahul Mazumder, Massachusetts Institute of Technology
Time: Saturday, 16:30–18:00
Room: LInC 268

16:30-17:00

Asymptotic comparison of q-norm regularized least squares

Arian Maleki, Columbia University

17:00-17:30

High-dimensional regression with L_0 regularization

Peter Radchenko, University of Southern California

17:30-18:00

Advanced Mixed Integer Programming Formulations for Non-Convex Optimization Problems in Statistical Learning

Juan Pablo Vielma, Massachusetts Institute of Technology

Big Data in Biological Sciences

Organizer: Sharmodeep Bhattacharyya, Oregon State University
Chair: Sharmodeep Bhattacharyya, Oregon State University
Time: Saturday, 16:30–18:00
Room: LInC 210

16:30-17:00

The Union of Intersections (UoI) Method for Interpretable Data Driven Discovery and Prediction

Kristofer Bouchard, Lawrence Berkeley National Laboratory

17:00-17:30

Neyman-Pearson (NP) classification algorithms and NP receiver operating characteristic (NP-ROC) curves

Jessica Li, University of California, Los Angeles

17:30-18:00

Adjusting for gene-gene correlation in gene-set tests in expression data

Duo Jiang, Oregon State University

Statistical Inference with Complex Data : Beyond Normality Assumption

Organizer: Rajarshi Mukherjee, Stanford University
Chair:  Sanjay Chaudhuri, National University of Singapore
Time: Saturday, 16:30–18:00
Room: LInC 228

16:30-17:15

Classification of distributions by tail heaviness

Javier Rojo, University of Nevada, Reno

17:15-18:00

Odds Ratios and Singular Values

M. B. Rao, University of Cincinnati

Learning and Predictive Models for Complex Systems

Organizer: Xiaohui Chang, Oregon State University
Chair: Yunjin Choi, Stanford University
Time: Saturday, 16:30–18:00
Room: LInC 302

16:30-17:00

Unsupervised learning with generalized split-and-recombine

Dongseok Choi, Oregon Health and Science University; President, KISS

17:00-17:30

Random forest models for the probable biological condition of streams and rivers in the USA

Eric Fox, United States Environmental Protection Agency

17:30-18:00

Mastering Feng Shui in Graph-Based Business Survival Prediction

Xiaohui Chang, Oregon State University

Statistical Challenges in Clinical Trial: Trend and Innovation

Organizer: Satrajit Roychoudhury, Novartis Pharmaceuticals
Chair: Vipin Arora, Eli Lilly and Company
Time: Saturday, 16:30–18:00
Room: LInC 345

16:30-17:00

Bayesian Adaptive Two-Stage Design for early phase oncology Trial

Rong Liu, Bayer Healthcare

17:00-17:30

Reflections of statistical challenges in biomedical science and making difference in health care

Yulan Li, Medivation

17:30-18:00

Exact Trend Test on Comparing Tumor Incidence in Transgenic Mouse Carcinogenicity Studies

Lei Shu, Astellas Pharma US, Inc.

Computational methods for Bayesian model selection

Organizer: Vivekananda Roy, Iowa State University
Chair: Jyotishka Datta, Duke University
Time: Saturday, 16:30–18:00
Room: LInC 350

16:30-17:00

On the Choice of Prior Distributions for Bayesian Binary Regression Models

Joyee Ghosh, University of Iowa

17:00-17:30

Standard Errors, Regularization Paths and Selection of Tuning Parameters for Bayesian Lassos

Sounak Chakraborty, University of Missouri

17:30-18:00

Generalized importance sampling methods for estimating large number of Bayes factors

Vivekananda Roy, Iowa state University

Topics in theoretical statistics and Applied Probability

Organizer: Parthanil Roy, Indian Statistical Institute
Chair: Srinivasan Balaji, George Washington University
Time: Saturday, 16:30–18:00
Room: LInC 314

16:30-17:00

How Being Distributionally Robust Can Improve Learning In High Dimensions?

Karthyek Murthy, Columbia University

17:00-17:30

Optimal design and subdata selection for big data

John Stufken, Arizona State University

17:30-18:00

Stationarity as a Path Property–with Applications in Time Series Analysis

Yi Shen, University of Waterloo