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Sunday, 08/01/2010
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Simplex Techniques for Quantile Regression Model Selection
Yonggang Yao, SAS Institute
2:05 PM
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Variable Selection via the Lasso-Type Regularization for Structural Equation Models
Kei Hirose, Kyushu University; Sadanori Konishi, Kyushu University
2:50 PM
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Discovering Sparse Covariance Structures with the Isomap
Amy Wagaman, Amherst College; Elizaveta Levina, University of Michigan
5:05 PM
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Robust Parametric Classification and Variable Selection
Eric Chi, Rice University; David W. Scott, Rice University
5:05 PM
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Adaptive Estimation in High-Dimensional Response Surface Models via Iterative Thresholding Regularization
Samir Touzani, French Institut of Petroleum; Anestis Antoniadis, University Joseph Fourier; Daniel Busby, French Institut of Petroleum
5:20 PM
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Monday, 08/02/2010
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Global Regularization Under Constraints
Patrick Laurie Davies, University of Duisburg-Essen
8:35 AM
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Regularization Approach to Nonparametric Estimation in Multivariate Mixtures
Michael Levine, Purdue University; David Hunter, Penn State; Didier Chauveau, Université d'Orléans
8:55 AM
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Regularized REML for Estimation and Selection of Fixed and Random Effects in Linear Mixed-Effects Models
Sijian Wang, University of Wisconsin-Madison; Peter Song, University of Michigan; Ji Zhu, University of Michigan
10:35 AM
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Joint Inference of Sparse Network and Genetic Association in Genetical Genomics Studies
Hongzhe Li, University of Pennsylvania
11:00 AM
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Grouping and Selection Over a Network Specified by a Directed Graph
Xiaotong Shen, University of Minnesota; Hsin-Cheng Huang, Academia Sinica
11:50 AM
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Spectral Regularization Algorithms for Learning Large Incomplete Matrices
Rahul Mazumder, Stanford University; Trevor Hastie, Stanford University; Rob Tibshirani, Stanford University
2:05 PM
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Tuesday, 08/03/2010
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Identification of Neural Functional Connectivity Using a Sparse Generalized Volterra Model
Dong Song, University of Southern California; Theodore W. Berger, University of Southern California
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Regularized Gaussian Mixture Modeling with Adaptive Covariance Shrinkage
Hyang Min Lee, Penn State; Jia Li, Penn State
9:55 AM
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Variable Selection for Multiply-Imputed Data
Qixuan Chen, Columbia University; Sijian Wang, University of Wisconsin-Madison
10:55 AM
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P-Values for Classification in High-Dimensional Settings
Niki Zumbrunnen, University of Bern; Lutz Dümbgen, University of Bern
11:05 AM
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Reduced-Rank Factor Models for Network and Relational Array Data
Peter Hoff, University of Washington
2:05 PM
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Wednesday, 08/04/2010
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Regularization for Stationary Multivariate Time Series
Yan Sun, University of Cincinnati; Xiaodong Lin, Rutgers University
9:05 AM
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Functional Mixed Effects Modeling by Parameter Cascading
Jiguo Cao, Simon Fraser University; James Owen Ramsay, McGill University
10:35 AM
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Regularized Variance Estimation and Variance Stabilization of High-Dimensional Data
Jean-Eudes J. Dazard, Case Western Reserve University; J. Sunil Rao, Case Western Reserve University
11:05 AM
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Structured Penalties for Generalized Functional Linear Models (GFLM)
Jaroslaw Harezlak, Indiana University School of Medicine; Tim Randolph, Fred Hutchinson Cancer Research Center; Ziding Feng, Fred Hutchinson Cancer Research Center
11:15 AM
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Reduced-Rank Stochastic Regression with a Sparse Singular-Value-Decomposition: Modeling Larval Drift Effects on Cod Population Dynamics as a Case Study
Kun Chen, The University of Iowa; Kung-Sik Chan, The University of Iowa; Nils Christian Stenseth, Centre for Ecological and Evolutionary Synthesis
11:50 AM
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Variable Selection via Smoothing Spline Adaptive Response Transformation
Wenxuan Zhong, University of Illinois
11:55 AM
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Regularization, Sparsity, and Rank Restrictions in High-Dimensional Regression
Alan Julian Izenman, Temple University
2:05 PM
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A Unified Framework for High-Dimensional Analysis of M-estimators with Decomposable Regularizers
Pradeep Ravikumar, The University of Texas at Austin; Sahand Negahban, University of California, Berkeley; Martin Wainwright, University of California, Berkeley; Bin Yu, University of California, Berkeley
2:30 PM
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