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Keyword Search Criteria: High dimension returned 51 record(s)
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Sunday, 07/29/2018
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Empirical Bayes Analysis of Overdispersed High-Dimensional Protein Interaction Data
Anna Reisetter
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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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Empirical Bayes Analysis of Overdispersed High-Dimensional Protein Interaction Data
Anna Reisetter
2:30 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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Partial Distance Correlation Screening for High-Dimensional Time Series
Kashif Yousuf, Columbia University; Yang Feng, Columbia University
4:05 PM
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Robust Nonparametric Tests for Imaging Databased on Data Depth
Julia Wrobel, Columbia University; Sara Lopez-Pintado, Columbia University
5:05 PM
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Monday, 07/30/2018
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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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Structured Mixture of Linear Mappings in High Dimension
Chun-Chen Tu, University of Michigan; Florence Forbes, INRIA; Benjamin Lemasson, Universit ´e Grenoble; Naisyin Wang, U of Michigan
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Random Dual Rotation: Generalized Permutation Test for High Dimension, Low Sample Size Data
Hee Cheol Chung, University of Georgia; Jeongyoun Ahn, University of Georgia
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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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Coverage Probability of Empirical Likelihood for Dependent Data
Guangxing Wang, University of California, Davis; Wolfgang Polonik, University of California, Davis
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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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Using Modified Competitive Swarm Optimizer to Find D-Optimal Designs for Complicated Logistic Models
Zizhao Zhang, UCLA; Weng Kee Wong, UCLA
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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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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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Coverage Probability of Empirical Likelihood for Dependent Data
Guangxing Wang, University of California, Davis; Wolfgang Polonik, University of California, Davis
9:30 AM
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Multilinear Low-Rank Vector Autoregressive Modeling via Tensor Decomposition
Di Wang, University of Hong Kong; Guodong Li, University of Hong Kong; Dr. LIAN Heng, City University of Hong Kong
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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Using Modified Competitive Swarm Optimizer to Find D-Optimal Designs for Complicated Logistic Models
Zizhao Zhang, UCLA; Weng Kee Wong, UCLA
10:45 AM
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Posterior Convergence and Coverage Aspects of Gaussian Process Approximations
Biraj Subhra Guha, Texas A & M University; Debdeep Pati, Texas A&M University
10:50 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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A Joint Analysis of Brain Signal, Genetics, and Behavior
Zhaoxia Yu, UCI; Hernando Ombao, King Abdullah University of Science and Technology; Dustin Pluta, University of California, Irvine; Tong Shen, University of California, Irvine
11:00 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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Understanding Cryptocurrency Price Formation from Time Series of Local Blockchain Graph Features
Cuneyt Akcora, University of Texas at Dallas; Asim Dey, University of Texas at Dallas; Ceren Abay, University of Texas at Dallas; Yulia Gel, University of Texas at Dallas; Umar Islambekov, University of Texas at Dallas; Murat Kantarcioglu, University of Texas at Dallas
11:25 AM
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Infer the in Vivo Point of Departure with ToxCast in Vitro Assay Data Using a Robust Learning Approach
Dong Wang, FDA National Center for Toxicological Research (NCTR)
11:35 AM
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A Concentration Inequality for Large Autocovariance Matrices
Yicheng Li, University of Washington; Fang Han, University of Washington
11:50 AM
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Nonparametric Mediation Analysis for Investigating the ROle of Microbiome Health
Kyle Carter, University of Arizona; Meng Lu, University of Arizona; Lingling An, University of Arizona
11:50 AM
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A Cluster Elastic Net for Multivariate Regression
Ben Sherwood, University of Kansas; Bradley S Price, West Virginia University
2:50 PM
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Tuesday, 07/31/2018
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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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The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks
Arjun Sondhi, University of Washington; Ali Shojaie, University of Washington
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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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 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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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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A Fast Algorithm with Minimax Optimal Guarantees for Topic Models with an Unknown Number of Topics
Florentina Bunea, Cornell Univeristy
2:55 PM
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Hyperplane Estimation in High Dimensions
Zhiyuan Lu, University of Michigan
3:20 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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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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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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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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Variable Selection via Partial Correlation
Runze Li, Penn State University; Jingyuan Liu, Xiamen University; Lejie Lou, Ernst & Young
11:05 AM
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A Robust and Efficient Approach to Causal Inference Based on Sparse Sufficient Dimension Reduction
Shujie Ma, UC Riverside-Dept of Statistics
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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A Functional Dependence Measure for Large Curve Time Series with an Application to Autoregressions
Xinghao Qiao, LSE; Shaojun Guo, Renmin University of China
3:05 PM
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