Keyword Search
Legend:
CC = Colorado Convention Center H = Hyatt Regency Denver at Colorado Convention Center
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: Sparsity returned 39 record(s)
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Monday, 07/29/2019
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Sparse SIR: Optimal Rates and Adaptive Estimation
Kai Tan
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Bayesian Covariance Estimation for Large Spatial Data
Brian Kidd, Texas A&M University; Matthias Katzfuss, Texas A & M University
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Edge Deletion Tests in Graphical Models for Multivariate Time Series
Marco Reale, University of Canterbury; Chris Price, University of Canterbury; Anna Lin, Statistics New Zealand; Rory Ellis, University of Canterbury
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Comparing Time Series Graphical Lasso and Sparse VAR Algorithms
Aramayis Dallakyan, Texas A&M University; Rakheon Kim, Texas A&M University; Mohsen Pourahmadi, Texas A&M University
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Sparse Functional Principal Component Analysis in High Dimensions
Xiaoyu Hu, peking university; Fang Yao, peking university
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Inference for Measurement Error Model Under High-Dimensional Settings
Mengyan Li, Penn State University; Yanyuan Ma, The Pennsylvania State University
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HIV Prevalence in Key Populations: a Semiparametric Bayesian Hierarchical Model for Scarce and Imbalanced Data
Amy Zhang, Pennsylvania State University; Le Bao, Pennsylvania State University; Michael Daniels, University of Florida
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Multi-Scale Vecchia Approximations of Gaussian Processes
Jingjie Zhang, Texas A&M University; Matthias Katzfuss, Texas A & M University
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Comparing Time Series Graphical Lasso and Sparse VAR Algorithms
Aramayis Dallakyan, Texas A&M University; Rakheon Kim, Texas A&M University; Mohsen Pourahmadi, Texas A&M University
8:35 AM
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Sparse Functional Principal Component Analysis in High Dimensions
Xiaoyu Hu, peking university; Fang Yao, peking university
9:00 AM
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Inference for Measurement Error Model Under High-Dimensional Settings
Mengyan Li, Penn State University; Yanyuan Ma, The Pennsylvania State University
9:30 AM
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Principal Component-Guided Sparse Regression
Kenneth Tay, Stanford University; Jerome Friedman, Stanford University; Robert Tibshirani, Stanford University
9:50 AM
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Wald I: Statistical Learning with Sparsity
Trevor J. Hastie, Stanford University
10:35 AM
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Structured Shrinkage Priors
Maryclare Griffin, Cornell University Center for Applied Mathematics; Peter Hoff, Duke University
10:35 AM
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Multi-Scale Vecchia Approximations of Gaussian Processes
Jingjie Zhang, Texas A&M University; Matthias Katzfuss, Texas A & M University
10:50 AM
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Sparse Canonical Correlation Analysis via Iterative Thresholding
Joseph Poythress, University of Georgia; Jeongyoun Ahn, University of Georgia; Cheolwoo Park, University of Georgia
11:05 AM
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HIV Prevalence in Key Populations: a Semiparametric Bayesian Hierarchical Model for Scarce and Imbalanced Data
Amy Zhang, Pennsylvania State University; Le Bao, Pennsylvania State University; Michael Daniels, University of Florida
11:15 AM
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Sparse Generalized Principal Component Analysis: Algorithms and Their Applications
Jianhao Zhang, Ohio State University; Yoonkyung Lee, Ohio State University
11:35 AM
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Detecting Interpretable Insights from Large-Scale Time Series Data
Qing Feng, Facebook; Sean Taylor , Facebook
3:05 PM
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Tuesday, 07/30/2019
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Joint Association and Classification Analysis of Multi-View Data
Yunfeng Zhang, Texas A&M University; Irina Gaynanova, Texas A&M Univeristy
10:55 AM
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Gaussian Copula Vector Autoregressive Modeling
Vladas Pipiras, University of North Carolina At Chapel Hill; James Livsey, U.S. Census Bureau; Benjamin Leinwand, University of North Carolina at Chapel Hill
11:15 AM
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SIDA: a New Discriminant Analysis Method for Multi-Type, Multi-Class Data
Sandra Safo, University of Minnesota; Eun Jeong Min, University of Pennsylvania
11:35 AM
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Debiased Inference in High-Dimensional Single-Index Models Under Gaussian Design
Hamid Eftekhari, University of Michigan; Moulinath of Banerjee, university of michigan; Ya'acov Ritov, university of michigan
11:50 AM
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Experimental Design in the Pharmaceutical Industry
Brad Evans, Pfizer, Inc
2:05 PM
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Wald II: Statistical Learning with Sparsity
Trevor J. Hastie, Stanford University
2:05 PM
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Penalized Basis Models for Very Large Spatial Data Sets
Mitchell Krock, University of Colorado at Boulder; William Kleiber, University of Colorado; Stephen Becker, University of Colorado
2:20 PM
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Sparse Vector Networks
Victor Solo, University of New South Wales
2:20 PM
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Wednesday, 07/31/2019
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Mixture Prior for Sparse Signals with Dependent Covariance Structure
Ling Wang, Michigan State University
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Inferring Complex Phylogenetic Networks Efficiently
Cora Allen-Coleman, University of Wisconsin - Madison; Cécile Ané, University of Wisconsin - Madison
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Bayesian Homogeneity Pursuit with Thresholded Dirichlet Process Priors
Andrew Whiteman, University of Michigan; Jian Kang, University of Michigan
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Wald III: Statistical Learning with Sparsity
Trevor J. Hastie, Stanford University
10:35 AM
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Simultaneous Change Point Detection and Structure Recovery for High-Dimensional Gaussian Graphical Models
Yufeng Liu, University of North Carolina at Chapel Hill
11:25 AM
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Bayesian Sparse Signal Recovery: Gaussian Models and Beyond
Jyotishka Datta, University of Arkansas
2:05 PM
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A Fully-Bayesian Approach to Sparse Reduced-Rank Multivariate Regression
Dunfu Yang, Kansas State University; Gyuhyeong Goh, Kansas State University; Haiyan Wang, Kansas State University
2:05 PM
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Spike-And-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models
Ray Bai; Gemma Moran, University of Pennsylvania; Joseph Antonelli, University of Florida
2:50 PM
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