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Sunday, 08/04/2013
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Cluster Pruning: Finding a Better Cluster Representative Object by Dimension Reduction
Amy Wagaman, Amherst College
2:05 PM
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On Efficient Dimension Reduction with Respect to a Statistical Functional of Interest
Wei Luo, Pennsylvania State University; Bing Li, The Pennsylvania State University; Xiangrong Yin, University of Georgia
2:35 PM
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Tensor Sliced Inverse Regression and Its Asymptotics
Shanshan Ding, University of Minnesota; Dennis Cook, University of Minnesota
2:50 PM
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Tensor Dimension Reduction for Chemical Sensing
Wenxuan Zhong, University of Illinois at Urbana-Champaign
2:55 PM
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Dimension Reduction for Sparse Functional Data
Edwin Kam Fai Lei, University of Toronto; Fang Yao, University of Toronto; Yichao Wu, NC State University
3:05 PM
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Monday, 08/05/2013
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Data Expo 2013: What Attaches People to Their Community?
Xiaoyue Cheng, Iowa State University; Dianne H. Cook, Iowa State University
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On Testing Common Indices for Two Multi-Index Models
Xuejing Liu; Zhou Yu, University of Wisconsin; Xuerong Meggie Wen, Department of Mathematics and Statistics, Missouri University of Science and Technology; Robert Paige, Department of Mathematics and Statistics, Missouri University of Science and Technology
8:35 AM
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Bayesian Smoothing Spline ANOVA for Binary Response with Dimension Reduction
Chin-I Cheng; Paul Speckman, Univ. of Missouri-Columbia
8:50 AM
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Robust Non-Negative Matrix Factorization Procedures for Analyzing Tumor and Face Image Data
Jiayang Sun, Case Western Reserve University; Kenneth Lopiano, SAMSI; S. Stanley Young, National Institute of Statistical Sciences
8:55 AM
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New Ideas for Sufficient Dimension Reduction for Functional Data
James Wright
9:05 AM
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Robust Dimension Reduction in Regression Using Divergences
Tharuvai Sriram, Univ of Georgia
10:35 AM
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Variable Length Markov Chains for Sequential Prediction in Dependence Time Series
Abraham J Wyner, The Wharton School, University of Pennsylvania; Joshua Magarick, University of Pennsylvania
10:35 AM
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Regularized Canonical Correlation and Application to High-Dimensional Biomarker Data with Survival Endpoint
Li Liu, Sanofi
11:20 AM
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Tuesday, 08/06/2013
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Model-Based Classifications of High-Throughput Data Review, Design, and Application to a Cancer Clinical Study
AC Cambon, Department of Bioinformatics and Biostatistics, University of Louisville; Shesh Nath Rai, University of Louisville
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Manifold Learning: Nonlinear Dimension Reduction Sans Distortion
Dominique Perrault-Joncas, Amazon.com; Marina Meila, University of Washington
9:55 AM
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Probability-Enhanced Sufficient Dimension Reduction for Binary Classification
Seung Jun Shin, North Carolina State University; Yichao Wu, NC State University; Hao Helen Zhang, North Carolina State University; Yufeng Liu, The University of North Carolina
10:35 AM
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A Novel Principal Component Analysis for Spatially Misaligned Multivariate Air Pollution Data
Roman Jandarov, University of Washington; Adam Szpiro, University of Washington
11:35 AM
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Manifold Regression for Functional Data
Andrew Farris, UC Davis; Hans-Georg G. Müller, University of California, Davis
11:55 AM
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On Multilinear Principal Component Analysis of Order-Two Tensors
I-Ping Tu, Academia Sinica; Hung Hung, Institute of Epidemiology and Preventive Medicine, National Taiwan University; Su-Yun Huang, Institute of Statistical Science, Academia Sinica; Peishien Wu, Institute of Statistical Science, Academia Sinica
2:05 PM
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Adaptively Weighted Large Margin Classifiers for Sufficient Dimension Reduction
Andreas Artemiou, Michigan Technological University; Yufeng Liu, The University of North Carolina
2:25 PM
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Sufficient Dimension Reduction in Binary Classification
Seung Jun Shin, North Carolina State University; Yichao Wu, NC State University; Hao Helen Zhang, University of Arizona; Yufeng Liu, The University of North Carolina
3:20 PM
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Wednesday, 08/07/2013
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Nonparametric Intervention Time Series Modeling
Jin-Hong Park, College of Charleston
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Data-Driven Algorithms for Dimension Reduction in Causal Inference
Emma Persson; Ingeborg Waernbaum, Umeå University; Jenny Häggström, Umeå University; Xavier de Luna, Umeå University
8:35 AM
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Variable Selection in Complex High-Dimensional Data Based on Principal Fitted Components
Moumita Karmakar, University of Maryland Baltimore County; Kofi Placid Adragni, University of Maryland, Baltimore County
8:50 AM
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Model-Based Clustering for Multivariate Binary Data with Dimension Reduction
Michio Yamamoto, Osaka University; Kenichi Hayashi, Osaka University Graduate School of Medicine
9:20 AM
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Dimension Reduction in Functional Data Classification
Santiago Velilla, Universidad Carlos III
10:35 AM
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Recent Developments in Gradient-Enhanced Kriging
Peter Marcy, University of Wyoming
3:20 PM
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Thursday, 08/08/2013
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Computational Techniques for High-Dimensional Nonparametric Bayes
Anjishnu Banerjee
8:35 AM
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Exploratory and Inferential Methods for Massive Data
Naomi S. Altman, Pennsylvania State University; Wei Luo, Pennsylvania State University; Garvesh Raskutti, SAMSI
9:00 AM
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Projective Method for Dimension Reduction with Multivariate Responses
Armine Bagyan, The Pennsylvania State University; Arkady Tempelman, The Pennsylvania State University; Bing Li, The Pennsylvania State University
9:50 AM
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A Bayesian Spatio-Functional Clustering Model Based on Wavelet Smoothing, with Application to Climate Change Study
Zhen Zhang, Michigan State University; Chae Young Lim, Michigan State; Tapabrata Maiti, Michigan State University
10:35 AM
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