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Key:
Applications
Computational Statistics
Computing Science
Data Science
Data Visualization
Machine Learning
Thursday, May 17
CS05 -
Statistical Machine Learning with Business Applications
Invited
Thu, May 17, 10:30 AM - 12:00 PM
Regency Ballroom A
Organizer(s): Brad Price, West Virginia University
Chair(s): Brad Price, West Virginia University
10:30 AM
A Cluster Elastic Net for Multivariate Regression
Ben Sherwood, University of Kansas
11:00 AM
Selection and Its Inference Using the Whole Solution Paths
Peng Wang, University of Cincinnati
11:30 AM
Shrinking Characteristics of Precision Matrix Estimators
Aaron J. Molstad, Fred Hutchinson Cancer Research Center
CS07 -
Optimization
Contributed
Thu, May 17, 10:30 AM - 12:00 PM
Lake Fairfax B
Chair(s): Jingyi Zhu, The Johns Hopkins University
10:30 AM
Topological Mixture Estimation
Presentation
Steve Huntsman, BAE Systems
10:45 AM
Plotting Two-Dimensional Confidence Regions
Presentation
Christopher Weld, College of William & Mary
11:00 AM
Tracking Capability of Stochastic Approximation Algorithms with Constant Gain
Jingyi Zhu, The Johns Hopkins University
11:15 AM
Variable Selection for Consistent Clustering
Ronald Joseph Yurko, Carnegie Mellon University
11:30 AM
BRISC: Bootstrap for Rapid Inference on Spatial Covariances
Arkajyoti Saha, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
11:45 AM
Reduced Complexity of Second-Order Simultaneous Perturbation Stochastic Approximation Algorithms
Jingyi Zhu, The Johns Hopkins University
CS12 -
Model Selection in High-Dimensions with Complexities
Invited
Thu, May 17, 1:30 PM - 3:00 PM
Regency Ballroom A
Organizer(s): Hamparsum Bozdogan, University of Tennessee
Chair(s): Hamparsum Bozdogan, University of Tennessee
1:30 PM
A New Approach to Dimension Reduction For Multivariate Time Series
Chung Eun Lee, University of Tennessee, Knoxville
2:00 PM
Coordinate-Independent Sparse Estimation in Semiparametric Models
Haileab Hilafu, University of Tennessee
2:30 PM
Expected Volume Confidence Region Complexity (EVCR_COMP) Criterion in High Dimensions with Applications
Hamparsum Bozdogan, University of Tennessee
CS18 -
Nonlinear Dimension Reduction
Invited
Thu, May 17, 3:30 PM - 5:00 PM
Regency Ballroom A
Organizer(s): Michael Trosset, Indiana University
Chair(s): Michael Trosset, Indiana University
3:30 PM
Optimality of the Johnson-Lindenstrauss Lemma
Jelani Nelson, Harvard University
4:00 PM
Matrix Sketching for Alternating Direction Method of Moments Optimization
Presentation
Daniel McDonald, Indiana University
4:30 PM
Optimal Dimensionality Reduction for Non-Linear Clustering Via Nystrom Approximation
Presentation
Alex Gittens, Rensselaer Polytechnic Institute
CS24 -
TensorFlow
Invited
Thu, May 17, 5:15 PM - 6:15 PM
Regency Ballroom A
Organizer(s): Tim Hesterberg, Google
Chair(s): Tim Hesterberg, Google
5:15 PM
TensorFlow Autograph: Source Code Transformation for Easier TensorFlow
Alex Wiltschko, Google
5:45 PM
Machine Learning with TensorFlow and R
J.J. Allaire, Rstudio
Friday, May 18
CS31 -
Recent Advances in Statistical Machine Learning
Invited
Fri, May 18, 10:30 AM - 12:00 PM
Regency Ballroom A
Organizer(s): Eric Chi, North Carolina State University; David Scott, Rice University
Chair(s): David Scott, Rice University
10:30 AM
On the Regularizations for Enforcing Equi-Sparsity
Yiyuan She, Florida State Univresity
11:00 AM
An Alternating Directions Method for Large-scale Multivariate Convex Regression
Jason Xu, University of California Los Angeles
11:30 AM
Tensor Canonical Correlation Analysis
Eric Chi, North Carolina State University
CS38 -
Statistical Challenges in Large-Scale Data Mining
Invited
Fri, May 18, 1:30 PM - 3:00 PM
Regency Ballroom A
Organizer(s): Tian Zheng, Columbia University
Chair(s): Tian Zheng, Columbia University
1:30 PM
A Scalable Algorithm for Change-Points Computation in Large Graphical Models
Yves Atchade, University of Michigan
2:00 PM
Embedding Approaches for Mining Heterogeneous Information Networks
Presentation
Yizhou Sun, UCLA
2:30 PM
Approximate Data Analytics
Christopher Jermaine, Rice University
CS45 -
Statistical Machine Learning Applications in Surveys
Invited
Fri, May 18, 3:30 PM - 5:00 PM
Regency Ballroom A
Organizer(s): Wendy Martinez, U.S. Bureau of Labor Statistics
Chair(s): Wendy Martinez, U.S. Bureau of Labor Statistics
3:30 PM
Classification and Regression Trees and Forests for Imputing Data from Sample Surveys
Presentation
MoonJung Cho, U.S. Bureau of Labor Statistics
4:00 PM
Model-Assisted Survey Estimation With Modern Prediction Techniques
Jean Opsomer, Colorado State University
4:30 PM
Calling All Stakeholders: Developing a Demographic Statistical Redesign Agenda
Richard Levy, US Census Bureau
CS51 -
Predictive Big Data Analytics
Invited
Fri, May 18, 5:15 PM - 6:15 PM
Regency Ballroom A
Organizer(s): Jim Harner, West Virginia University
Chair(s): Jim Harner, West Virginia University
5:15 PM
Interpretable Machine Learning
Presentation
Patrick Hall, H2O.ai
5:45 PM
Big Data with R
Presentation
Edgar Ruiz, Rstudio
Saturday, May 19
CS55 -
New Directions in Rank Data Aggregation and Modeling
Invited
Sat, May 19, 8:30 AM - 10:00 AM
Grand Ballroom D
Organizer(s): Michael G. Schimek, Medical University of Graz
Chair(s): William F. Wieczorek, SUNY Buffalo State
8:30 AM
The Bayesian Mallows Model for Analysing Ranks and Preference Data: From Genomics to Recommendation Systems
Valeria Vitelli, University of Oslo
9:00 AM
Detecting and Interpreting Median Constrained Bucket Orders Within the Kemeny Axiomatic Framework
Antonio D'Ambrosio, University of Naples Federico II
9:30 AM
Discussant
Michael G. Schimek, Medical University of Graz
CS62 -
Machine Learning for Complex Data
Contributed
Sat, May 19, 10:30 AM - 12:00 PM
Grand Ballroom D
Chair(s): David Marchette, Naval Surface Warfare Center
10:30 AM
A Classification Tree for Functional Data
Jan Gertheiss, Clausthal University of Technology
10:45 AM
Optimal Estimation for Varying Coefficient Model with Longitudinal Data
Xiaowu Dai, University of Wisconsin Madison
11:00 AM
Regression Trees and Ensemble Methods for Multivariate Outcomes
Evan Lee Reynolds, University of Michigan
11:15 AM
XPCA: Interval-Censored Copula Principal Component Analysis for Discrete and Continuous Features
Clifford Anderson-Bergman, Sandia National Laboratories
11:30 AM
The Two-to-Infinity Norm and Singular Subspace Geometry With Applications to High-Dimensional Statistics
Joshua Cape, Johns Hopkins University
11:45 AM
Floor Discussion
CS67 -
Feature Selection
Contributed
Sat, May 19, 1:15 PM - 2:45 PM
Grand Ballroom D
Chair(s): Soren Harner, MuleSoft
1:15 PM
Statistical Testing for Feature Relevance: The HARVEST Algorithm
Presentation
Herbert I Weisberg, Causalytics LLC
1:30 PM
Supervised Clustering via an Implicit Network for High Dimensional Data
Brandon Woosuk Park, George Mason University
1:45 PM
Variable Selection for the Recurrent Event Data with Broken Adaptive Ridge Regression
Dayu Sun, University of Missouri-Columbia
2:00 PM
Feature Selection in L0 Norm: A Viable Approach
Ana Maria Kenney, Pennsylvania State University
2:15 PM
Robust Surrogate Ridge Estimators for Linear Regression Model Based on an M-Estimator and MM-Estimator
Presentation
Osama A Hussien, Alexandria University Egypt
2:30 PM
Floor Discussion
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