Keyword Search
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CC = Vancouver Convention Centre F = Fairmont Waterfront Vancouver
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: sparsity returned 36 record(s)
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Sunday, 07/29/2018
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Ranked Sparsity Methods for Transparent Model Selection
Ryan Andrew Peterson, University of Iowa; Joseph Cavanaugh, University of Iowa
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Factor GARCH-Ito Models for High-Frequency Data with Application to Large Volatility Matrix Prediction
Donggyu Kim, KAIST; Jianqing Fan, Princeton University
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Multi-Scale Vecchia Approximation of Gaussian Processes
Jingjie Zhang, Texas A&M University; Matthias Katzfuss, Texas A&M University
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Sparse Convex Clustering
Binhuan Wang, New York University School of Medicine; Yilong Zhang, Merck Research Laboratories; Will Wei Sun, University of Miami School of Business Administration; Yixin Fang, New Jersey Institute of Technology
2:05 PM
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Ranked Sparsity Methods for Transparent Model Selection
Ryan Andrew Peterson, University of Iowa; Joseph Cavanaugh, University of Iowa
2:35 PM
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Factor GARCH-Ito Models for High-Frequency Data with Application to Large Volatility Matrix Prediction
Donggyu Kim, KAIST; Jianqing Fan, Princeton University
2:45 PM
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Nonparametric Empirical Bayes Methods for High Dimension Problems
Linda Zhao, University of Pennsylvania; Junhui Cai, University of Pennsylvania
2:55 PM
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Toward a Sampling Theory for Statistical Network Analysis
Harry Crane, Rutgers
3:05 PM
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Multi-Scale Vecchia Approximation of Gaussian Processes
Jingjie Zhang, Texas A&M University; Matthias Katzfuss, Texas A&M University
3:10 PM
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Monday, 07/30/2018
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Covariate-Adjusted Tensor Classification in High-Dimensions
Yuqing Pan, Florida State University; Qing Mai, Florida State University; Xin Zhang, Florida State University
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A Probabilistic Tool for Assessing the Laplace Approximation: Review, Optimization, and GPU Implementation
Shaun McDonald, Simon Fraser University; David Campbell, Simon Fraser University
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Bayesian Model Selection for Markov Chains Using Sparse Probability Vectors
Matthew Heiner, UC Santa Cruz; Athanasios Kottas, UC Santa Cruz; Stephan Munch, NOAA
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Bayesian Regression Tree Ensembles That Adapt to Smoothness and Sparsity
Antonio Ricardo Linero, Florida State University; Yun Yang, Florida State University
9:25 AM
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Two-Way Sparsity for Time-Varying Networks, with Applications in Genomics
Thomas Bartlett, University College London; Ricardo Silva, University College London; Ioannis Kosmidis, University of Warwick
9:50 AM
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Regularized Estimation of High-Dimensional Spectral Density
Sumanta Basu, Cornell University
9:55 AM
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Sparse Single Index Models for Multivariate Responses
Yuan Feng, North Carolina State University; Luo Xiao, North Carolina State University; Eric Chi, North Carolina State University
10:35 AM
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Neuronized Priors for A Unified Sparsity Inference
Ismael Castillo, Universite Pierre et Marie Curie - Paris 6; Minsuk Shin, Harvard University
11:00 AM
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Bayesian Model Selection for Markov Chains Using Sparse Probability Vectors
Matthew Heiner, UC Santa Cruz; Athanasios Kottas, UC Santa Cruz; Stephan Munch, NOAA
12:00 PM
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Sparse-Input Neural Networks for High-Dimensional Nonparametric Regression and Classification
Jean Feng; Noah Simon, University of Washington
2:05 PM
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The Inverse Gamma-Gamma Pior for Optimal Posterior Contraction and Multiple Hypothesis Testing
Ray Bai, University of Florida; Malay Ghosh, University of Florida
2:25 PM
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Dynamic Variable Selection with Spike-And-Slab Process Priors
Kenichiro McAlinn, University of Chicago; Veronika Rockova, University of Chicago
2:45 PM
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Cross-Validation for Dependent Multiple Testing
Josh Price, University of Arkansas; Jyotishka Datta, University of Arkansas
3:35 PM
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Tuesday, 07/31/2018
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Bayesian Inference in Nonparanormal Graphical Models
Jami Mulgrave; Subhashis Ghosal, North Carolina State University
9:35 AM
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Structural Learning and Integrative Decomposition of Multi-View Data
Irina Gaynanova, Texas A&M Univeristy; Gen Li, Columbia University
10:55 AM
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Supervised Principal Component Regression for Functional Data with High-Dimensional Predictors
Xinyi Zhang, University of California, Berkeley; Dehan Kong, University of Toronto; Qiang Sun, University of Toronto
11:15 AM
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Large Numbers of Explanatory Variables
Heather Battey, Imperial College London; David Cox, Nuffield College
2:30 PM
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Wednesday, 08/01/2018
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Fast Bayesian Sparse Learning via Thresholding Priors
Andrew Whiteman, University of Michigan; Jian Kang, University of Michigan
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High-Dimensional Change Point Estimation via Sparse Projection
Tengyao Wang, University of Cambridge; Richard J Samworth, University of Cambridge
8:35 AM
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A General Framework for Vecchia Approximations of Gaussian Processes
Matthias Katzfuss, Texas A&M University; Joseph Guinness, North Carolina State University
9:05 AM
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Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interactions
Tianxi Cai, Harvard T.H. Chan School of Public Health; Yin Xia, Fudan University; Tianwen Cai, University of Pennsylvania
10:35 AM
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Fusion Learning with High-Dimensionality
Xin Gao, York University; Raymond J. Carroll, Texas A & M University
10:50 AM
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Inferring Non-Bifurcating Phylogenies with the Adaptive Lasso
Vu Dinh, University Of Delaware
10:55 AM
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Can We Compute an Optimal Sparse Decision Tree?
Cynthia Rudin, Duke University; Elaine Angelino, Berkeley; Nicholas Larus-Stone, Cambridge; Margo Seltzer, Harvard; Daniel Alabi, Harvard
3:05 PM
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Thursday, 08/02/2018
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Generalized Score Matching for Non-Negative Data
Shiqing Yu, University of Washington; Mathias Drton, University of Washington; Ali Shojaie, University of Washington
8:50 AM
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Bayesian Analysis with Orthogonal Matrix Parameters
Michael Jauch, Duke University; Peter Hoff, Duke University; David B Dunson, Duke University
11:05 AM
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Sparse Multi-Class Vector AutoRegressive Models
Ines Wilms, KU Leuven; Christophe Croux, EDHEC Business School; Luca Barbaglia, KU Leuven
11:35 AM
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