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32 Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-142
Nonparametric Methods with High-Dimensional Data — Contributed Papers
Section on Nonparametric Statistics
Chair(s): Xuerong Wen, Missouri University of Science and Technology
2:05 PM Variable Selection Using Kernel Partial Correlation Coefficient
Zhen Huang, Columbia University; NABARUN DEB, Columbia University; Bodhisattva Sen, Columbia University
2:20 PM Dimension Reduction Through Influence Function Methods
Wei Lin, Ohio University; Prabha Shrestha, Drake University
2:35 PM On Forward Sufficient Dimension Reduction for Categorical and Ordinal Responses
Harris Quach, Pennsylvania State University; Bing Li, Penn State University
2:50 PM Accuracy of the Bootstrap and the Normal Approximation in a High-Dimensional Framework
Mayya Zhilova, Georgia Institute of Technology
3:05 PM Adaptive Testing in High Dimension
Runmin Wang, Southern Methodist University; Xiaofeng Shao, University of Illinois at Urbana-Champaign; Yangfan Zhang, University of Illinois at Urbana-Champaign
3:20 PM Plugin Estimation of Smooth Optimal Transport Maps and Wasserstein Distances
Tudor Manole, Carnegie Mellon University; Sivaraman Balakrishnan, Carnegie Mellon University; Jonathan Niles-Weed, New York University; Larry Wasserman, Carnegie Mellon University
3:35 PM An Efficient Computational Method for Causal Inference in High-Dimensional Data: Neighborhood-Based Cross Fitting
Oluwagbenga David Agboola, University of Northern Colorado