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Keyword Search Criteria: High-dimensional returned 132 record(s)
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Sunday, 07/29/2018
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Approximate Bayesian Computation with Complex High-Dimensional Data and Limited Simulations
Taylor Gene Pospisil, Carnegie Mellon University
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Efficient Robust Doubly Adaptive Regularized Regression with Application to fMRI Data
Wei Tu, University of Alberta
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Inference for Fine-Gray Competing Risks Model with High-Dimensional Covariates
Jue Hou, UCSD Biostatistics; Jelena Bradic, UC San Diego; Ronghui Xu, UC San Diego
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Tailoring PCA for Detecting Sparse Changes in Multi-Stream Data
Martin Tveten, University of Oslo; Ingrid Kristine Glad, University of Oslo
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Empirical Bayes Analysis of Overdispersed High-Dimensional Protein Interaction Data
Anna Reisetter
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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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High-dimensional Cost-constrained Regression via Non-convex Optimization
Yufeng Liu, University of North Carolina at Chapel Hill
2:05 PM
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Genetic Analysis of High-Dimensional Phenotypes
Michael Philip Epstein, Emory University
2:25 PM
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High-Dimensional MCMC Diagnostics with Application to Spatial Text Clustering of Beer Flavours
David Alexander Campbell, Simon Fraser University; Subhash Lele, University of Alberta; Peter Solymos, Alberta Biodiversity Monitoring
2:25 PM
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Tailoring PCA for Detecting Sparse Changes in Multi-Stream Data
Martin Tveten, University of Oslo; Ingrid Kristine Glad, University of Oslo
2:30 PM
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Empirical Bayes Analysis of Overdispersed High-Dimensional Protein Interaction Data
Anna Reisetter
2:30 PM
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High-Dimensional Gaussian Graphical Model for Network-Linked Data
Ji Zhu, University of Michigan; Boang Liu, University of Michigan; Tianxi Li, University of Michigan; Cheng Qian, University of Michigan; Elizaveta Levina, University of Michigan
2:45 PM
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Significance Testing in Non-Sparse High-Dimensional Linear Models
Yinchu Zhu, University of Oregon; Jelena Bradic, UC San Diego
2:50 PM
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Debiasing the Debiased Lasso with Bootstrap
Sai Li, Rutgers University
3:05 PM
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Inference for Fine-Gray Competing Risks Model with High-Dimensional Covariates
Jue Hou, UCSD Biostatistics; Jelena Bradic, UC San Diego; Ronghui Xu, UC San Diego
3:15 PM
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Asymptotic Behavior of the Alpha-Risk Minimizing Portfolio in High-Dimensional Setting
Hiroyuki Taniai, Waseda University
3:20 PM
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Partial Distance Correlation Screening for High-Dimensional Time Series
Kashif Yousuf, Columbia University; Yang Feng, Columbia University
4:05 PM
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Estimation of Dynamic Conditional Correlation Matrices by a Nonlinear Common Factor Model
Craig Rolling, Saint Louis University; Yongli Zhang, Independent Researcher; Yuhong Yang, University of Minnesota
4:05 PM
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Weak Signals in High-Dimension Regression: Detection, Estimation and Prediction
Yi Li
4:05 PM
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Nonparametric Estimation of Sufficient Forecasting Using High-Dimensional Predictors
Xiufan Yu, Penn State University; Jiawei Yao, Citadel LLC; Lingzhou Xue, Penn State University and National Institute of Statistical Sciences
4:25 PM
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Monday, 07/30/2018
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A Doubly Distributed and Integrated Method of Moments for High-Dimensional Correlated Data Analysis
Emily Charlotte Hector, University of Michigan; Peter X.-K. Song, University of Michigan
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SurvBoost: An R Package for High-Dimensional Variable Selection in the Stratified Proportional Hazards Model via Gradient Boosting
Emily Morris, University of Michigan; Jian Kang, University of Michigan; Zhi He, University of Michigan; Yanming Li, University of Michigan; Yi Li, University of Michigan
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EAinference: An R Package for Simulation-Based Inference via Estimator Augmentation
Seunghyun Min, UCLA; Qing Zhou, UCLA
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Hierarchical-Block Conditioning Approximations for High-Dimensional Multivariate Normal Probabilities
Jian Cao, King Abdullah University of Science and Technology; Marc G Genton, King Abdullah University of Science and Technology; David E Keyes, King Abdullah University of Science and Technology; George Turkiyyah, King Abdullah University of Science and Technology
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Asymptotic Properties of Adaptive Group Lasso in High-Dimensional Generalized Additive Model with a Diverging Number of Parameters and Consistent Tuning Parameter Selection
Kaixu Yang; Jun Liu, Michigan State University
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Honest Confidence Sets for High-Dimensional Linear Regression by Projection and Shrinkage
Kun Zhou, University of California, Los Angeles; Qing Zhou, UCLA
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Bayesian Inference in High-Dimensional Linear Regression Using an Empirical Correlation-Adaptive Prior
Chang Liu, North Carolina State University; Yue Yang, North Carolina State University; Howard D Bondell, University of Melbourne; Ryan Martin, North Carolina State University
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Bayesian Sparse Regression in the Presence of Nuisance Parameters
Seonghyun Jeong, North Carolina State University; Subhashis Ghoshal, North Carolina State Univeristy
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Discriminant Analysis for High-Dimensional Spatio-Temporal Data
Rejaul Karim, Michigan State University; Taps Maiti, Michigan State University; Chae Young Lim, Seoul National University
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Variable Selection with Missing Data Imputation in the High-Dimensional Setting
Soeun Kim, The University of Texas Health Science Center at Houston; Yunxi Zhang, The University of Texas Health Science Center at Houston
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Factor Models for High-Dimensional Dynamic Networks: With Application to International Trade Flow Time Series 1981--2015
Elynn CHEN, Rutgers University; Rong Chen, Rutgers University
8:35 AM
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Evaluating Statistical Classifiers for Detecting C9orf72 Amyotrophic Lateral Sclerosis Patients Based on Whole Blood RNAseq Data
Wenting Wang, Biogen; Guolin Zhao, Biogen; Feng Gao, Biogen; Tzu-Ying Liu, University of Michigan; Ayla Ergun, Biogen; Jessica Hurt, Biogen
8:50 AM
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Building a Genomic Signature via Transfer Learning on Both Labelled and Unlabelled High-Dimensional Data: a Case Study in Predicting Prostate Cancer Metastasis
Yang Liu, GenomeDx Biosciences; Hossein Sharifi-Noghabi, Simon Fraser University; Nicholas Erho, GenomeDX Biosciences; Raunak Shrestha, Vancouver Prostate Centre; Mohammed Alshalalfa, GenomeDX Biosciences; Elai Davicioni, GenomeDX Biosciences; Colin Collins, Vancouver Prostate Centre; Martin Ester, Simon Fraser University
9:05 AM
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New Methods for Threshold Variable Identification and Estimation in Threshold Dynamic Factor Models
Xialu Liu, San Diego State University; Rong Chen, Rutgers University
9:15 AM
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Regularized Estimation of High-Dimensional Spectral Density
Sumanta Basu, Cornell University
9:55 AM
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Joint Testing in High-Dimensional Instrumental Variables Regression with an Application to Genomics Data
Jiarui Lu, University of Pennsylvania; Hongzhe Li, University of Pennsylvania
10:35 AM
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Variable Selection with Missing Data Imputation in the High-Dimensional Setting
Soeun Kim, The University of Texas Health Science Center at Houston; Yunxi Zhang, The University of Texas Health Science Center at Houston
10:35 AM
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Bootstrapping Maxima of High-Dimensional Random Vectors with Variance Decay
Miles Lopes, University of California, Davis; Hans Mueller, UC Davis; Zhenhua Lin, University of Toronto
10:50 AM
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Supervised Clustering via an Implicit Network for High-Dimensional Data
Brandon Park; Anand N Vidyashankar, George Mason University; Tucker S McElroy, U.S. Census Bureau
11:05 AM
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Discriminant Analysis for High-Dimensional Spatio-Temporal Data
Rejaul Karim, Michigan State University; Taps Maiti, Michigan State University; Chae Young Lim, Seoul National University
11:05 AM
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Asymptotic Independent U-Statistics in High-Dimensional Adaptive Testing
Yinqiu He, University of Michigan; Gongjun Xu, University of Michigan; Chong Wu, University of Minnesota; Wei Pan, University of Minnesota
11:20 AM
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Ultra-High-Dimensional Single-Index Models for Longitudinal Data
Brittany Green, University of Cincinnati; Yan Yu, University of Cincinnati; Dr. LIAN Heng, City University of Hong Kong
11:35 AM
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A Factor Augmented Vector Autoregressive Model Under High-Dimensional Scaling
George Michailidis, University of Florida; Jiahe Lin, University of Michigan
2:05 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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Structure Learning for Phylogenetic Tree with Quantitative Characters
Chaoyu Yu; Mathias Drton, University of Washington
2:20 PM
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Statistical Inference for High-Dimensional Time Series
Ruey S Tsay, University of Chicago, Booth School of Business
2:30 PM
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PULasso: High-Dimensional Variable Selection with Presence-Only Data
Hyebin Song, UW-Madison
3:05 PM
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Tuesday, 07/31/2018
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Analysis Framework in Integrating Data of Different Modalities with Application in Identifying Important Predictors/Subgroups in Non-Alcoholic Steatohepatitis
Tuan Nguyen, Gilead Sciences; Guang Chen, Gilead Sciences; Adarsh Joshi, Gilead Sciences, Inc.; Lulu Wang, Gilead Sciences; Yafeng Zhang, Gilead Sciences; Yuanyuan Xiao, Gilead Sciences; Catherine Jia, Gilead Sciences; Ren Xu, Gilead Sciences; Stephen Djedjos, Gilead Sciences; Rob Myers, Gilead Sciences
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Sparse Causal Dynamic Network Modeling of fMRI
Xuefei Cao, Brown University; Xi Luo, Brown University; Bjorn Sandstede, Brown University
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Incorporating Genetic Network into Case-Control Association Studies with High-Dimensional DNA Methylation Data
Hokeun Sun, Pusan National University
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Bayesian Inference for Sample Surveys in the Presence of High-Dimensional Auxiliary Information
Yutao Liu, Columbia University; Andrew Gelman, Columbia University; Qixuan Chen, Columbia University
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A Direct Approach to High-Dimensional Error-In-Variables Regression
Yunan Wu, University of Minnesota; Lan Wang, University of Minnesota
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A Modified Approach to Component-Wise Gradient Boosting for High-Dimensional Regression Models
Brandon Butcher, University of Iowa; Brian J. Smith, University of Iowa
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Visualizing Dependence in High Dimensions
Marius Hofert, University of Waterloo; Wayne Oldford, University of Waterloo
8:35 AM
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Scrutiny of Inference on Generalized Linear Models with High-Dimensional Covariates
Lu Xia, University of Michigan; Bin Nan, University of California, Irvine; Yi Li, University of Michigan
8:35 AM
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Sequential Change-Point Detection Based on Nearest Neighbors
Hao Chen, University of California, Davis
9:00 AM
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Improved Selection of High-Dimensional Neuroimaging Biomarkers Associated with Neurodegenerative Disease Progression
Tanya Garcia, Texas A&M University; Jeffrey S Morris, The University of Texas M.D. Anderson Cancer Center
9:15 AM
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Projection-Based Inference for High-Dimensional Linear Models
Sangyoon Yi, Texas A&M Univ; Xianyang Zhang, Texas A&M University
9:20 AM
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Incorporating Genetic Network into Case-Control Association Studies with High-Dimensional DNA Methylation Data
Hokeun Sun, Pusan National University
9:35 AM
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Bayesian Regression for High-Dimensional Data Using a Prior on the Model Fit
Howard D Bondell, University of Melbourne
9:35 AM
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Generalized CP and the Bootstrap for Variable Selection in Moderate or High-Dimensional Data
Lawrence D Brown, University of Pennsylvania; Junhui Cai, University of Pennsylvania; Linda Zhao, University of Pennsylvania
10:35 AM
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Inference on Average Treatment Effect with Repeated Data Splitting in High Dimensions
Jingshen Wang, University of Michigan; Xuming He, University of Michigan; Gongjun Xu, University of Michigan
10:35 AM
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Simple Bootstrap and Simulation Approaches to Quantifying Reliability of High-Dimensional Feature Selection
Frank Harrell, Vanderbilt University, Dept of Biostatistics
10:35 AM
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High-Dimensional Sparse Generalized Eigenvalue Problem and Its Applications to Multivariate Statistics
Kean Ming Tan, University of Minnesota; Zhaoran Wang, Northwestern University; Han Liu, Northwestern University; Tong Zhang, Tencent Technology
10:50 AM
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Analysis of Time-Course Microbiota Data Through Longitudinal Linear Combination Test
Elham Khodayari Moez, University of Alberta; Morteza Hajihosseini, University of Alberta; Anita Kozyrskyj, University of Alberta; Irina Dinu, University of Alberta
10:50 AM
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Bayesian Inference for Sample Surveys in the Presence of High-Dimensional Auxiliary Information
Yutao Liu, Columbia University; Andrew Gelman, Columbia University; Qixuan Chen, Columbia University
11:15 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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A Direct Approach to High-Dimensional Error-In-Variables Regression
Yunan Wu, University of Minnesota; Lan Wang, University of Minnesota
11:40 AM
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A Modified Approach to Component-Wise Gradient Boosting for High-Dimensional Regression Models
Brandon Butcher, University of Iowa; Brian J. Smith, University of Iowa
11:45 AM
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Estimating Directed Acyclic Graphs from High-Dimensional Data and Its Application in Biomarker Discoveries in Early Clinical Trials
Hua Zhong, New York University; Jaehong Yu, NYU School of Medicine
11:55 AM
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Nonparametric Inference on L\'Evy Measures of L\'Evy-Driven Ornstein-Uhlenbeck Processes
Daisuke Kurisu
12:05 PM
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High-Dimensional Sign Tests for the Direction of a Skewed Single-Spiked Distribution
Davy Paindaveine, Université libre de Bruxelles; Thomas Verdebout, Université libre de Bruxelles
2:05 PM
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Change-Detection-Assisted Multiple Testing for Spatiotemporal Data
Lilun Du, HKUST; Yunlong Wang, Nankai University; Changliang Zou, Nankai University; Zhaojun Wang, Nankai University
2:05 PM
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A Stochastic Approach for Downscaling Solar Irradiance Data Products
Wenqi Zhang, University of Colorado at Boulder; William Kleiber, University of Colorado
2:05 PM
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Gaussian Variational Approximation for High-Dimensional State Space Models
Robert Kohn, Univ of New South Wales; Matias Quiroz , University of New South wales ; David J Nott, National University of Singapore
2:05 PM
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Quantifying the Reliability of Image Replication Studies
Ciprian Crainiceanu, Johns Hopkins University
2:05 PM
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Finite Sample Change Point Inference and Identification for Hig-Dimensional Mean Vectors
Mengjia Yu, University of Illinois at Urbana-Champaign; Xiaohui Chen, University of Illinois at Urbana-Champaign
2:20 PM
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Dynamic, Personalized Instruments via Responsive Matrix Sampling with High-Dimensional Covariates
Sean Taylor, Facebook; Curtiss Cobb, Facebook; Chelsea Zhang, UC Berkeley
2:35 PM
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Simulation-Selection-Extrapolation Estimator for High-Dimensional Errors-In-Variables Models
Linh Nghiem, Southern Methodist University; Cornelis Potgieter, Southern Methodist University
2:50 PM
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Change-Point Estimation of Trend in High-Dimensional Time Series
Monika Bhattacharjee , University of Florida; Moulinath Banerjee, University of Michigan; George Michailidis, University of Florida
2:50 PM
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Bayesian Spatial Process Models for High-Dimensional Finite Population Sampling
Sudipto Banerjee, UCLA School of Public Health; Alec Goldstein-Chan, University of California Los Angeles
2:55 PM
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Complexity Results for MCMC Derived from Quantitative Bounds
Jun Yang, University of Toronto; Jeffrey S Rosenthal, University of Toronto
3:05 PM
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Finding Needles in a Hay Stack - an Approach for a Small-Number-Factor High-Dimensional Data
Chi-Hse Teng
3:05 PM
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Spatial Factor Models for High-Dimensional and Large Spatial Data: An Application in Forest Variable Mapping
Daniel Taylor Rodriguez, Portland State University; Andrew Oliver Finley, Michigan State University; Abhi Datta, Johns Hopkins Bloomberg School of Public Health; Chad Babcock, University of Washington; Hans-Erik Andersen, USDA Forest Service; Bruce Douglas Cook, NASA Goddard Space Flight Center; Douglas C Morton, NASA Goddard Space Flight Center; Sudipto Banerjee, UCLA School of Public Health
3:35 PM
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Wednesday, 08/01/2018
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Accounting for Unobserved Covariates with Varying Degrees of Estimability in High-Dimensional Data
Chris McKennan, University of Chicago; Dan Nicolae, University of Chicago
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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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Inferences in High-Dimensional Misspecified Mixed Model Analysis for GWAS
Cecilia Dao, Yale Univ; Jiming Jiang, University of California, Davis; Debashis Paul, UC Davis; Hongyu Zhao, Yale
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A Hierarchical, Multiple-Testing Framework for High-Dimensional Data Analysis and Application to Flow Cytometry
John Pura
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Bayesian Analysis of High-Dimensional Point Pattern Data Sets Using Latent Multivariate Log-Gamma Random Vectors
Heli Gao, Florida State University
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Bayesian High-Dimensional Multi-Outcome Regression with Tree-Structured Shrinkage
Emma Grace Thomas, Harvard T.H. Chan School of Public Health; Francesca Dominici, Harvard T. H. Chan School of Public Health; Giovanni Parmigiani , Harvard T.H. Chan School of Public Health / Dana-Farber Cancer Institute; Lorenzo Trippa, Harvard
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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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Convergence Complexity Analysis of Albert and Chib's Algorithm
Qian Qin, University of Florida; James P. Hobert, University of Florida
8:35 AM
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Imputed Factor Regression for High-Dimensional Block-Wise Missing Data
Yanqing Zhang, Yunnan University; Niansheng Tang, Yunnan University; Annie Qu, University of Illinois at Urbana-Champaign
8:50 AM
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Component-wise Discrete Asymmetric AdaBoost for High-dimensional Binary Quantile Regression
Tae-Hwy Lee, Univ of California, Riverside; Jianghao Chu, University of California, Riverside; Aman Ullah, University of California, Riverside
8:50 AM
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MCMC for High-Dimensional Bayesian Regression
Dootika Vats
8:55 AM
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Can We Train Machine Learning Methods to Outperform the High-Dimensional Propensity Score Algorithm?
Mohammad Ehsanul Karim, University of British Columbia; Robert W Platt, McGill University
9:20 AM
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A Functional Neural Network for Genetic Data Analysis Involving High-Dimensional Multivariate Outcomes
Shan Zhang, Michigan State University; Xiaoxi Shen; Xiaoran Tong, Michigan State University; Qing Lu, Michigan State University
9:20 AM
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Joint Hierarchical Models for Sparsely Sampled High-Dimensional LiDAR and Forest Variables
Andrew Oliver Finley, Michigan State University; Hans-Erik Andersen, USDA Forest Service; Sudipto Banerjee, UCLA School of Public Health; Bruce Douglas Cook, NASA Goddard Space Flight Center; Abhi Datta, Johns Hopkins Bloomberg School of Public Health; Douglas C Morton, NASA Goddard Space Flight Center
9:35 AM
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Bayesian High-Dimensional Multi-Outcome Regression with Tree-Structured Shrinkage
Emma Grace Thomas, Harvard T.H. Chan School of Public Health; Francesca Dominici, Harvard T. H. Chan School of Public Health; Giovanni Parmigiani , Harvard T.H. Chan School of Public Health / Dana-Farber Cancer Institute; Lorenzo Trippa, Harvard
9:35 AM
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Bayesian Analysis of High-Dimensional Point Pattern Data Sets Using Latent Multivariate Log-Gamma Random Vectors
Heli Gao, Florida State University
9:50 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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Sparse Quadratic Classification Rules via Linear Dimension Reduction
Tianying Wang, Texas A & M University; Irina Gaynanova, Texas A&M Univeristy
10:35 AM
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Discovering Depression Subtypes with High-Dimensional Eigenvalue Estimation on Resting-State fMRI Data
Samprit Banerjee, Weill Medical College, Cornell University
10:35 AM
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Estimation and Inference for the Indirect Effect in High-Dimensional Linear Mediation Models
Ruixuan Zhou, University of Illinois at Urbana-Champaign; Liewei Wang, Mayo Clinic; Dave Zhao, University of Illinois at Urbana-Champaign
10:50 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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Adaptive Mantel Test for Penalized Inference, with Applications to Imaging Genetics
Dustin Pluta, University of California, Irvine; Tong Shen, University of California, Irvine; Hernando Ombao, King Abdullah University of Science and Technology; Zhaoxia Yu, University of California, Irvine
10:55 AM
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High-Dimensional Regression for Microbiome Compositional Data
Xiaohan Yan, Cornell University; Jacob Bien, University of Southern California; Christian Mueller, Flatiron Institute
11:05 AM
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Sparse Model Identification and Learning for Ultra-High-Dimensional Additive Partially Linear Models
Xinyi Li; Lily Wang, Iowa State University; Dan Nettleton, Iowa State University
11:05 AM
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High-Dimensional Discrimination with Trace Regularization
Jeongyoun Ahn, University of Georgia; Yongho Jeon, Yonsei University; Hee Cheol Chung, University of Georgia
11:15 AM
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Penalized Jackknife Empirical Likelihood in High Dimension
Na Zhao; jinfeng Xu, The University of Hong Kong
11:35 AM
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Bayesian Variable Selection Using Spike and Slab Prior with Application to High-Dimensional EEG Data by Local Modeling
Shariq Mohammed, University of Connecticut; Dipak Kumar Dey, University of Connecticut; Yuping Zhang, University of Connecticut
11:50 AM
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The Two-To-Infinity Norm and Singular Subspace Geometry with Applications to High-Dimensional Statistics
Joshua Cape, Johns Hopkins; Dept. of Applied Math and Statistics; Minh Tang, Johns Hopkins University; Carey E Priebe, Johns Hopkins University
2:05 PM
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Forecasting Consumer Interests from Search Query Data Using Large-Scale, Semiparametric Probabilistic Prediction Algorithms
Georg Goerg
2:05 PM
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Improved Robust Estimation of the Residual Scale in High-Dimensional Problems with the Adaptive Elastic Net S-Estimator for Efficient Robust Penalized Linear Regression Methods
David Kepplinger, University of British Columbia; Ezequiel Smucler, University of British Columbia; Gabriela V. Cohen Freue, University of British Columbia
2:05 PM
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High-Dimensional Markowitz Portfolio Optimization Problem: Empirical Comparison of Covariance Matrix Estimators
Johan Lim, Seoul National University; Young-Geun Choi, Fred Hutchinson Cancer Research Center; Sujung Choi, Soongsil University
2:05 PM
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Robust Outlier Detection for Low and High-Dimensional Neuroimaging Data with Principal Components Analysis and Split-Half Resampling
Derek Beaton, Baycrest Health Sciences; Kelly M Sunderland, Baycrest Health Sciences; Abiramy Uthirakumaran, Baycrest Health Sciences; Stephen R Arnott, Baycrest Health Sciences; Robert Bartha, Robarts Research; Sandra E Black, Sunnybrook Health Sciences Centre; Leanne Casaubon, Krembil Research Institute; Morris Freedman, Baycrest Health Sciences; Richard H Swartz, Sunnybrook Health Sciences Centre; Sean Symons, Sunnybrook Health Sciences Centre; ONDRI Investigators, ONDRI; Malcolm A Binns, Baycrest Health Sciences; Stephen C Strother, Baycrest Health Sciences
2:05 PM
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Direct Estimation of Differential Networks Under High-Dimensional Nonparanormal Graphical Models
Qingyang Zhang, University of Arkansas
2:20 PM
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Finding Best Low Dimensional Angles for Visualizing High-Dimensional Data
Yanming Di, Oregon State University; Wanli Zhang, Oregon State University
3:05 PM
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Dimension Reduction of High-Dimensional Data Sets Based on Stepwise SVM
Elizabeth Chou, National Chengchi University; Tzu-Wei Ko, National Chengchi University
3:35 PM
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Thursday, 08/02/2018
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Bayesian Spectral Analysis of High-Dimensional Time Series
Ori Rosen, Univ of Texas at El Paso; Rob Krafty, University of Pittsburgh
9:05 AM
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Extended Ensemble Kalman Filters for High-Dimensional Hierarchical State-Space Models
Jonathan Stroud, Georgetown University; Matthias Katzfuss, Texas A&M University; Christopher K. Wikle, University of Missouri
9:15 AM
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Probabilistic Predictive Principal Component Analysis for Spatially-Misaligned and High-Dimensional Air Pollution Data with Missing Observations
Phuong T Vu, University of Washington; Adam A Szpiro, University of Washington
9:35 AM
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A Non-Collapsing Particle Filter for a High-Dimensional Cellular Automata Model of Traffic Flow
Thomas Bengtsson, Genentech
9:35 AM
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Non-Stationary High-Dimensional Time Series Networks for Brain Imaging Data
Ivor Cribben, University of Alberta
9:35 AM
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An Integrated Bayesian Nonparameteric Method for Clustering of High-Dimensional Mixed Data
Chetkar Jha, University of Missouri; Subharup Guha, University of Florida
9:50 AM
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High-Dimensional Variable Selection When Features Are Sparse
Jacob Bien, University of Southern California; Xiaohan Yan, Cornell University
10:35 AM
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Estimating the Error Variance in a High-Dimensional Linear Model
Guo Yu, Cornell University; Jacob Bien, University of Southern California
10:50 AM
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A Kernel-Based Neural Network for High-Dimensional Genetic Risk Prediction Analysis
Xiaoxi Shen; Xiaoran Tong, Michigan State University; Qing Lu, Michigan State University
11:05 AM
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Fresh Ideas for Tuning Parameter Calibration
Johannes Lederer, Ruhr-University Bochum
11:15 AM
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Regularized Calibrated Estimation of Propensity Scores with Model Misspecification and High-Dimensional Data
Zhiqiang Tan, Rutgers University
11:25 AM
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Embracing Experimental Design Thinking for Large-Scale Statistical Analysis
Peter Chien, University of Wisconsin-Madison
11:25 AM
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Bayesian Reversible-Jump Sequential Variable Selection Methodology for High-Dimensional Arrays of Paired Predictors, with Application in Assessing Added-Value in Proteomics Data.
Bart Mertens, Leiden University Medical Centre; Alexia Kakourou, Leiden University Medical Centre
11:35 AM
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