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Sessions Were Renumbered as of May 19.
Legend:
CC-W = McCormick Place Convention Center, West Building, CC-N = McCormick Place Convention Center, North Building
H = Hilton Chicago, UC= Conference Chicago at University Center
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: High-dimensional returned 135 record(s)
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Sunday, 07/31/2016
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Cascaded High-Dimensional Histograms: A Generative Approach to Density Estimation
Siong Thye Goh, MIT; Cynthia Rudin, Duke University
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Modeling Connectivity in High-Dimensional Time Series Data via Factor Analysis
Hernando Ombao, University of California at Irvine; Yuxiao Wang, University of California at Irvine; Chee-Ming Ting, Universiti Teknologi Malaysia
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A Fully Bayesian Strategy for High-Dimensional Hierarchical Modeling Using Massively Parallel Computing
William Landau, Iowa State University; Jarad Niemi, Iowa State University
2:05 PM
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The Spike and Slab Lasso
Veronika Rockova, The Wharton School; Edward I. George, The Wharton School
2:30 PM
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Estimating High-Dimensional Multi-Layered Networks Through Penalized Maximum Likelihood
George Michailidis, University of Florida
3:05 PM
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Bayesian Modeling and Inference for High-Dimensional Spatiotemporal Data Sets
Sudipto Banerjee, University of California at Los Angeles
4:05 PM
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New Integrative Paradigms of Personalized Medicine for Cancer
Kim-Anh Do, MD Anderson Cancer Center; Veera Baladandayuthapani, MD Anderson Cancer Center; Francesco Stingo, MD Anderson Cancer Center; Min Jin Ha, MD Anderson Cancer Center; Thierry Chekouo Tekougang, MD Anderson Cancer Center
4:05 PM
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Bayesian High-Dimensional Sparse Models with Unknown Symmetric Errors
Lizhen Lin, The University of Texas; Minwoo Chae, The University of Texas at Austin; David Dunson, Duke University
4:05 PM
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Longitudinal Gaussian Graphical Models for Autism Risk Gene Detection
Kevin Lin, Carnegie Mellon University
4:20 PM
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Graphlet Screening for High-Dimensional Variable Selection
Qi Zhang, University of Nebraska - Lincoln; Jiashun Jin, Carnegie Mellon University; Cun-Hui Zhang, Rutgers University
4:50 PM
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A Convex Framework for High-Dimensional Sparse Cholesky Selection with Convergence Guarantees
Syed Rahman, University of Florida; Kshitij Khare, University of Florida
5:05 PM
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Detecting Association to Precision Networks via Conditional Multi-Type Graphical Models
Yanming Li, University of Michigan; Kevin He, University of Michigan; Jian Kang, University of Michigan; Hyokyoung (Grace) Hong, Michigan State University; Ji Zhu, University of Michigan; Yi Li, University of Michigan
5:20 PM
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Monday, 08/01/2016
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Bernstein-Von Mises Theorem for Individual Entries in Sparse High-Dimensional Linear Regression
Dana Yang, Yale University
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EigenPrism: Inference for High-Dimensional Signal-to-Noise Ratios
Lucas Janson; Emmanuel Candes, Stanford University; Rina Foygel Barber, The University of Chicago
8:35 AM
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Sequential Multiple Testing for Variable Selection in High-Dimensional Linear Model
Xinping Cui, University of California at Riverside; Hailu Chen, University of California at Riverside
8:35 AM
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The Biglasso Package: Extending Lasso Model Fitting to Big Data in R
Yaohui Zeng, University of Iowa; Patrick Breheny, University of Iowa
8:35 AM
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Estimation of Functional Connectivity Among Neuron Ensembles via Hawkes Processes
Shizhe Chen, University of Washington; Eric Shae-Brown, University of Washington; Ali Shojaie, University of Washington; Daniela Witten, University of Washington
8:50 AM
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Mediation Analysis of High-Dimensional Human Microbiome Data in the Longitudinal Study
Huilin Li , New York University Langone Medical Center; Yilong Zhang, New York University; Martin J. Blaser, New York University
9:15 AM
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Modeling Micronuclei Count Data Using the Generalized Monotone Incremental Forward Stagewise Method: Application in Women with Breast Cancer
Rebecca Lehman, Virginia Commonwealth University; Colleen Jackson-Cook, Virginia Commonwealth University; Kellie J. Archer, Virginia Commonwealth University
9:20 AM
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Bernstein-Von Mises Theorem for Individual Entries in Sparse High-Dimensional Linear Regression
Dana Yang, Yale University
9:35 AM
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Deep Learning for Emulation in Uncertainty Quantification
Jared D. Huling, University of Wisconsin - Madison; Peter Qian, University of Wisconsin - Madison
9:50 AM
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Psychographic Market Segmentation with Very Large Number of Behavioral Factors
Atreyee Majumder, Michigan State University; Tapabrata Maiti, Michigan State University
9:50 AM
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Stochastic Optimization for High-Dimensional Mixed Effect Generalized Linear Models
Jun Guo, University of Michigan; Yves F. Atchade, University of Michigan
9:50 AM
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Truncation-Based Nearest Neighbors Imputation for High-Dimensional Data with Detection Limit Thresholds
Jasmit Shah, University of Louisville; Guy N. Brock, The Ohio State University; Shesh N. Rai, University of Louisville; Aruni Bhatnagar, University of Louisville
10:05 AM
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High-Dimensional Analysis of Spatial Count Data: A Penalized Estimating Equation Approach
Rejaul Karim, Michigan State University; Tapabrata Maiti, Michigan State University
10:05 AM
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Statistical Inference for High-Dimensional Linear Regression
Tony Cai, University of Pennsylvania; Zijian Guo, University of Pennsylvania
10:35 AM
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A Two-Sample Test for High-Dimensional Covariance Matrices via Sparse Principal Component Analysis
Lingxue Zhu, Carnegie Mellon University; Jing Lei, Carnegie Mellon University; Bernie Devlin, University of Pittsburgh School of Medicine; Kathryn Roeder, Carnegie Mellon University
10:35 AM
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Semiparametric Bayesian Analysis of High-Dimensional Censored Outcome
Chetkar Jha, University of Missouri; Yi Li, University of Michigan; Steven Melly, Harvard; Dr Subharup Guha, University of Missouri
10:50 AM
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Identifying Interactions Using Convex Optimization
Jacob Bien, Cornell University ; Robert Tibshirani, Stanford University; Noah Simon, University of Washington
10:55 AM
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Conditional Screening for Survival Data
Hyokyoung (Grace) Hong, Michigan State University; Jian Kang, University of Michigan; Yi Li, University of Michigan
11:00 AM
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Distributed Estimation and Inference with Statistical Guarantees
Heather Battey, Imperial College London; Jianqing Fan, Princeton; Han Liu, Princeton; Junwei Lu, Princeton; Ziwei Zhu, Princeton
11:00 AM
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On the Inference of the Spikes for the High-Dimensional Covariance Matrix Based on High-Frequency Data
Keren Shen; JIANFENG YAO, The University of Hong Kong; Wai Keung Li, The University of Hong Kong
11:05 AM
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Structure Testing for Sparse High-Dimensional Graphical Models: Lower Bounds and Algorithms
Matey Neykov, Princeton; Junwei Lu, Princeton; Han Liu, Princeton
11:05 AM
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A Penalized Quasi-Likelihood Approach for Variable Selection in High-Dimensional Spatially Correlated Binary and Count Data
Abdhi Sarkar, Michigan State University; Chae Young Lim, Seoul National University; Tapabrata Maiti, Michigan State University
11:05 AM
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Graphical LASSO with Auxiliary Information: Application to Neural Connectivity
Giuseppe Vinci, Carnegie Mellon University; Robert Kass, Carnegie Mellon University; Valerie Ventura, Carnegie Mellon University; Matthew A. Smith, University of Pittsburgh
11:05 AM
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Empirical Bayes Prediction Under Check Loss
Gourab Mukherjee, University of Southern California
11:15 AM
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Testing High-Dimensional Differential Matrices, with Applications to Detecting Schizophrenia Genes
Kathryn Roeder, Carnegie Mellon University; Lingxue Zhu, Carnegie Mellon University; Jing Lei, Carnegie Mellon University
11:25 AM
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Large-Scale Cluster Analysis Using Fusion Penalties
Trambak Banerjee, University of Southern California; Peter Radchenko, University of Southern California; Gourab Mukherjee, University of Southern California
11:35 AM
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Model-Based Regression Clustering for High-Dimensional Data
Emilie Devijver
11:35 AM
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Process-Based Hierarchical Models for Coupling High-Dimensional LiDAR and Forest Variables Over Large Geographic Domains
Andrew Finley, Michigan State University; Sudipto Banerjee, University of California at Los Angeles; Yuzhen Zhou, University of Nebraska - Lincoln; Bruce Cook, NASA
11:35 AM
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Biologically Pathway Information Incorporated Structured Model
Xuebei An, MD Anderson Cancer Center; Jianhua Hu, MD Anderson Cancer Center; Kim-Anh Do, MD Anderson Cancer Center
11:50 AM
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Some Properties of the One Group Prior for Sparse High-Dimensional Models
Jean-Bernard Salomond
11:55 AM
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A Bayesian High-Dimensional Couple-Based Latent Risk Model with an Application to Infertility
Zhen Chen, Eunice Kennedy Shriver National Institute of Child Health and Human Development; Beom Seuk Hwang, Chung-Ang University; Germaine M. Buck Louis, Eunice Kennedy Shriver National Institute of Child Health and Human Development; Paul Albert, Eunice Kennedy Shriver National Institute of Child Health and Human Development
12:05 PM
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Bayesian Visual Analytics: BaVA
Leanna House, Virginia Tech; Scotland Leman, Virginia Tech; Chao Han, SAS Institute
2:05 PM
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Sparse Mediation Analysis for High-Dimensional Mediators with Application of Neuroimaging and Methylation Data
Seonjoo Lee, Columbia University
2:05 PM
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Bayesian Regression Using a Prior on the Model Fit
Brian Naughton, North Carolina State University; Howard Bondell, North Carolina State University
2:20 PM
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High-Dimensional Linear Regression via the R2-D2 Shrinkage Prior
Yan Zhang, North Carolina State University; Brian J. Reich, North Carolina State University; Howard Bondell, North Carolina State University
2:35 PM
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Inference on High-Dimensional Sparse Poisson Means
Jyotishka Datta, Duke University/Statistical and Applied Mathematical Sciences Institute; David Dunson, Duke University
2:45 PM
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High-Dimensional Regularized Estimation in Time Series Under Mixing Conditions
Kam Chung Wong, University of Michigan; Ambuj Tewari, University of Michigan; Zifan Li, University of Michigan
2:50 PM
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Bayesian Feature Selection for Ultra-High-Dimensional Imaging Genetics Data
Yize Zhao, Statistical and Applied Mathematical Sciences Institute; Hongtu Zhu, The University of North Carolina at Chapel Hill; Fei Zou, University of Florida
3:25 PM
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Tuesday, 08/02/2016
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A Stability Analysis of Sparse K-Means
Abraham Apfel, University of Pittsburgh; Stewart J. Anderson, University of Pittsburgh
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Bayesian Method for Causal Inference in High-Dimensional Time Series with Applications to Sales Data
BO NING
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Regularized Efficient Score Estimation and Testing Approach in Low-Dimensional and High-Dimensional GLM
Lixi Yu, University of Iowa; Jian Huang, University of Iowa
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Multicategory Classification Using High-Dimensional Predictors with Applications to Studying Effects of Rice Genome
Arkaprava Roy, North Carolina State University; Subhashis Ghoshal, North Carolina State University
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High-Dimensional Cox Regression for Genome-Wide Assessment of the Prognostic Benefit of Somatic Mutations in Ovarian Cancer
Brandon Butcher, University of Iowa; Patrick Breheny, University of Iowa; Donghai Dai, University of Iowa
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High-Dimensional Inference for Partial Linear Models
Zhuqing Yu
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Modern Projection Pursuit Ellipse for High-Dimensional Data
Jang Ik Cho, Case Western Reserve University; Xiaoyan Wei, Case Western Reserve University; Jiayang Sun, Case Western Reserve University
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Predicting Job Application Success with Two-Stage, Bayesian Modeling of Features Extracted from Candidate-Role Pairs
Jon Krohn, untapt; Gabe Rives-Corbett, untapt; Ed Donner, untapt
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Lasso Adjustments of Treatment Effect Estimates in Randomized Experiments
Adam Bloniarz, University of California at Berkeley; Cun-Hui Zhang, Rutgers University; Hanzhong Liu, University of California at Berkeley; Jasjeet Sekhon, University of California at Berkeley; Bin Yu, University of California at Berkeley
8:35 AM
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Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interactions
Yin Xia, The University of North Carolina at Chapel Hill
8:35 AM
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Efficient Method to Optimally Identify Important Biomarkers for Disease Outcomes with High-Dimensional Data
Xiang Li, Columbia University; Shanghong Xie, Columbia University; Donglin Zeng, The University of North Carolina at Chapel Hill; Yuanjia Wang, Columbia University
8:35 AM
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Regularized LDA for High-Dimensional Data
Jeongyoun Ahn, University of Georgia; Yongho Jeon, Yonsei University
8:35 AM
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A General Theory of Hypothesis Tests and Confidence Regions for Sparse High-Dimensional Models
Yang Ning; Han Liu, Princeton
8:50 AM
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Testing Independence with High-Dimensional Correlated Samples
Xi Chen; Weidong Liu, Shanghai Jiao Tong University
8:55 AM
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Pathway Lasso: Estimate and Select Sparse Mediation Pathways with High-Dimensional Mediators
Yi Zhao, Brown University; Xi Luo, Brown University
9:05 AM
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Accuracy Assessment for High-Dimensional Linear Regression
Tony Cai, University of Pennsylvania; Zijian Guo, University of Pennsylvania
9:05 AM
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Ultra-High-Dimensional Variable Selection with Application to Normative Aging Study: DNA Methylation and Metabolic Syndrome
Grace Yoon; Yinan Zheng, Northwestern University; Zhou Zhang, Northwestern University; Haixiang Zhang, Tianjin University; Brian Joyce, Northwestern University; Wei Zhang, Northwestern University; Wenxin Jiang, Northwestern University; Lifang Hou, Northwestern University; Lei Liu, Northwestern University; Tao Gao, Northwestern University; Andrea Baccarelli, Harvard; Joel Schwartz, Harvard; Pantel S. Vokonas, Boston University
9:20 AM
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High-Dimensional Gaussian Copula Regression: Adaptive Estimation and Statistical Inference
Linjun Zhang, University of Pennsylvania; Tony Cai, University of Pennsylvania
9:20 AM
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CoCoLasso for High-Dimensional Error-in-Variables Regression
Abhirup Datta, University of Minnesota; Hui Zou, University of Minnesota
9:35 AM
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Tuning-free heterogeneity pursuit in massive networks
Zhao Ren, University of Pittsburgh; Yongjian Kang, University of Southern California; Yingying Fan, University of Southern California; Jinchi Lv, University of Southern California
9:35 AM
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Kernel Machine Methods for Genetic Studies with High-Dimensional and Complex Outcomes
Michael C. Wu, Fred Hutchinson Cancer Research Center; Xiang Zhan, Fred Hutchinson Cancer Research Center; Ni Zhao, Fred Hutchinson Cancer Research Center
9:50 AM
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Inherently High-dimensional Analysis with Indicator Saturation
Neil R. Ericsson, Federal Reserve Board
9:50 AM
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Packing Inference of Correlation for an Arbitrarily Large Number of Variables
Kai Zhang, The University of North Carolina at Chapel Hill
9:50 AM
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Risk Estimation for High-Dimensional Lasso Regression
Daniel McDonald, Indiana University; Darren Homrighausen, Colorado State University
9:50 AM
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A Neighborhood-Assisted Test for High-Dimensional Mean Vector
Yumou Qiu, University of Nebraska - Lincoln
9:55 AM
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Communication Over a Noisy Channel Using High-Dimensional Linear Regression with Gaussian Design
Cynthia Rush, Yale University; Adam Greig, University of Cambridge; Ramji Venkataramanan, University of Cambridge
10:05 AM
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Variable Reduction in High-Dimensional Vector Time Series
Tucker McElroy, U.S. Census Bureau
10:35 AM
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Modern Projection Pursuit Ellipse for High-Dimensional Data
Jang Ik Cho, Case Western Reserve University; Xiaoyan Wei, Case Western Reserve University; Jiayang Sun, Case Western Reserve University
10:40 AM
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Machine Learning Methods in High-Dimensional Branching Processes
Anand N. Vidyashankar, George Mason University
10:55 AM
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Efficient inference for genetic association studies with multiple outcomes
Hélène Ruffieux, Ecole Polytechnique Fédérale de Lausanne; Anthony C. Davison, Ecole Polytechnique Fédérale de Lausanne; Irina Irincheeva, Nestlé Institute of Health Sciences SA; Jörg Hager, Nestlé Institute of Health Sciences SA
11:00 AM
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Predicting Job Application Success with Two-Stage, Bayesian Modeling of Features Extracted from Candidate-Role Pairs
Jon Krohn, untapt; Gabe Rives-Corbett, untapt; Ed Donner, untapt
11:05 AM
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Testing Low-Dimensional Coefficients in High-Dimensional Heteroscedastic Linear Models
Honglang Wang, Indiana University Purdue University Indianapolis; Ping-Shou Zhong, Michigan State University; Yuehua Cui, Michigan State University
11:20 AM
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High-Dimensional Inference for Partial Linear Models
Zhuqing Yu
11:30 AM
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Learning High-Dimensional Discrete Multivariate Auto-Regressive Models
Garvesh Raskutti, University of Wisconsin - Madison
2:05 PM
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Optimal Detection of Weak Principal Components in High-Dimensional Data
Edgar Dobriban
2:05 PM
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Mediation Analysis of GWAS with High-Dimensional Data-Driven Prior Information
Sunduz Keles, University of Wisconsin - Madison; Qi Zhang, University of Nebraska - Lincoln; Constanza Rojo, University of Wisconsin - Madison
2:05 PM
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Integrative Analysis of Incompatible Data Sets with Different Resolutions Reveals Consistent Genetic Effects
Yuan Jiang, Oregon State University
2:25 PM
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Dynamic Factor Models and Reduced Rank Regression in High-dimensional Time Series
Tze Leung Lai, Stanford University; Ka Wai Tsang, The Chinese University of Hong Kong; Hongsong Yuan, Shanghai University of Finance and Economics
2:30 PM
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Module-Based Reconstruction of Gene Regulatory Network into Predictive Modeling for High-Dimensional Genomic Data
Rui Zhong, AbbVie; Xin Huang, AbbVie; Viswanath Devanarayan, AbbVie
2:35 PM
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Reconstruction of Directed Acyclic Graphs Networks Based on Prior Causal Ordering Information with Applications to Gene Regulatory Networks
Pei-Li Wang, University of Florida; George Michailidis, University of Florida
2:35 PM
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Convex Regularization for High-Dimensional Tensor Regression
Ming Yuan, University of Wisconsin; Garvesh Raskutti, University of Wisconsin - Madison
2:45 PM
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Sparse Bayesian Graphical Vector Autoregression For Risk Analysis
Daniel Felix Ahelegbey, Boston University; Monica Billio, University of Venice; Roberto Casarin, University of Venice
2:50 PM
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Wednesday, 08/03/2016
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The Key Role of Statistics in Neuroimaging: Challenges and Opportunities
DuBois Bowman, Columbia University
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Variable Selection and Direction Estimation for Single-Index Models via DC-TGDR Method
Xi Liu, Xiamen University; Shuangge Ma, Yale University; Wei Zhong, Xiamen University
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How to Ask Questions of Huge Data with Few Samples
David Dunson, Duke University
8:35 AM
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Statistical Learning Guided by Managerial Decision Making
Bo Li, Tsinghua University
8:35 AM
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Sparse Variable Selection Aiming at Minimum Prediction Error
Maarten Jansen, Université Libre de Bruxelles
9:00 AM
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Detecting EQTLs: A Fast Analysis Protocol Using High-Dimensional Sequencing Data
Kai Kammers, Johns Hopkins Bloomberg School of Public Health; Ingo Ruczinski, Johns Hopkins Bloomberg School of Public Health; Margaret A. Taub, Johns Hopkins Bloomberg School of Public Health; Joshua Martin, The GeneSTAR Program; Lisa R. Yanek, The GeneSTAR Program; Lewis Becker, The GeneSTAR Program; Rasika A. Mathias, The GeneSTAR Program; Jeffrey Leek, Johns Hopkins Bloomberg School of Public Health
9:05 AM
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Deep Spatial Learning for Forensic Geolocation with Microbiome Data
Neal Grantham; Brian J. Reich, North Carolina State University; Eric Laber, North Carolina State University
9:20 AM
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Goodness-of-Fit Tests for High-Dimensional Linear Regression
Rajen Dinesh Shah, University of Cambridge; Peter Bühlmann, ETH Zurich
9:25 AM
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Dirichlet Process Mixture Model for High-Dimensional Gene Expression Data
Eric Mittman, Iowa State University; Jarad Niemi, Iowa State University
9:50 AM
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Free Lunches with Sparse Bayesian Nonparametric Learning: A Probabilistic Exploration of Lower Dimensional Structure Discovery with Sparse High-Dimensional Data
Anjishnu Banerjee, Medical College of Wisconsin
10:05 AM
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Fitting Convex Sets to Data via Matrix Factorization
Venkat Chandrasekaran
10:35 AM
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An approximate L0-based variable selection method for high dimensional data
Zhihua Sun, Ocean University of China; Gang Li, University of California at Los Angeles
10:50 AM
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Statistical Methods for Integrating the Phylogenetic Tree in Microbiome Data Analysis
Jun Chen, Mayo Clinic; Jian Xiao, Mayo Clinic
11:00 AM
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Expandable Factor Analysis
Sanvesh Srivastava, University of Iowa; Barbara E. Engelhardt, Princeton; David Dunson, Duke University
11:05 AM
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Small-Area Estimation for High-Dimensional Non-Gaussian Dependent Data
Jonathan R. Bradley, University of Missouri; Scott H. Holan, University of Missouri; Christopher Wikle, University of Missouri
11:35 AM
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Pseudo-Value Method for Ultra-High-Dimensional Semiparametric Models with Life-Time Data
Tony Sit, The Chinese University of Hong Kong
11:35 AM
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Using Observed Outcomes to Design High-Dimensional Propensity Scores
Lo-Hua Yuan, Harvard; Luke Miratrix, Harvard University; Donald B. Rubin, Harvard
11:35 AM
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Analysis of Ultra-High-Dimensional Polycystic Ovary Syndrome Genome Using DC-RR
Jill Lundell, Utah State University; Guifang Fu, Utah State University
11:50 AM
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CoCoLasso for High-Dimensional Error-in-Variables Regression
Hui Zou, University of Minnesota; Abhirup Datta, University of Minnesota
2:05 PM
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Group Feature Selection in Ultrahigh-Dimensional Generalized Varying-Coefficient Linear Models
Songshan Yang; Runze Li, Penn State University
2:05 PM
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Batch Effects in Network Inference
Claire Ruberman
2:05 PM
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Prediction-Oriented Marker Selection (PROMISE) with Application to High-Dimensional Regression
Soyeon Kim, MD Anderson Cancer Center; J. Jack Lee, MD Anderson Cancer Center; Veera Baladandayuthapani, MD Anderson Cancer Center
2:20 PM
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Testing-Based Variable Selection for High-Dimensional Linear Models
Siliang Gong, The University of North Carolina at Chapel Hill; Kai Zhang, The University of North Carolina at Chapel Hill; Yufeng Liu, The University of North Carolina at Chapel Hill
2:20 PM
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A New Statistical Method for Longitudinal High-Dimensional Data Analysis
Yuping Zhang, University of Connecticut
2:25 PM
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Covariance-Insured Screening Methods for Ultrahigh-Dimensional Variable Selection
Yi Li, University of Michigan; Ji Zhu, University of Michigan; Jiashun Jin, Carnegie Mellon University; Kevin He, University of Michigan; Yanming Li, University of Michigan
2:30 PM
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A Regularization Scheme on Word Occurrence Rates That Improves Estimation and Interpretation of Topical Content
Edoardo M. Airoldi, Harvard
2:55 PM
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Privately Preserving Algorithms to Release Sparse High-Dimensional Histograms
Bai Li; Rebecca Steorts, Duke University
3:05 PM
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Collaborative Targeted Learning for Large-Scale and High-Dimensional Data
Cheng Ju, University of California at Berkeley; Mark van der Laan, University of California at Berkeley; Susan Gruber, Harvard T.H. Chan School of Public Health; Jessica Franklin, Brigham and Women's Hospital; Richard Wyss, Brigham and Women's Hospital; Wesley Eddings, Brigham and Women's Hospital; Sebastian Schneeweiss, Brigham and Women's Hospital
3:20 PM
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Thursday, 08/04/2016
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A Unified Modeling Framework for State-Related Changes in High-Dimensional Effective Brain Connectivity
Hernando Ombao, University of California at Irvine; Yuxiao Wang, University of California at Irvine; Chee-Ming Ting, Universiti Teknologi Malaysia
8:35 AM
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Testing for Differential Connectivity in High-Dimensional Networks
Sen Zhao, University of Washington; Ali Shojaie, University of Washington
9:00 AM
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Interpretable High-Dimensional Inference via Score Maximization with an Application in Neuroimaging
Simon Vandekar, University of Pennsylvania; Philip Reiss, New York University; Russell Shinohara, University of Pennsylvania
9:20 AM
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HVAR: High-Dimensional Forecasting via Interpretable Vector Autoregression
David Matteson, Cornell University; William B. Nicholson, Cornell University ; Jacob Bien, Cornell University
9:25 AM
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A Simultaneous Variable Selection and Clustering Method for High-Dimensional Multinomial Regression Model
Sheng Ren, University of Cincinnati; Jason Lu, Cincinnati Children's Hospital Research Foundation; Emily Lei Kang, University of Cincinnati
9:35 AM
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Classification of Multivariate Time Series Data with Applications to ECIS
Laura Tupper, Cornell University; David Matteson, Cornell University
9:35 AM
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Projection Test for High-Dimensional Mean Vectors with Optimal Direction
Runze Li, Penn State University; Yuan Huang, Yale University; Lan Wang, University of Minnesota; Chen Xu, University of Ottawa
10:35 AM
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High-Dimensionality Effects on the Efficient Frontier
Rituparna Sen, Indian Statistical Institute
10:35 AM
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Cascaded High-Dimensional Histograms and an Application to Criminology
Siong Thye Goh, MIT; Cynthia Rudin, Duke University
10:35 AM
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A Genomically Informed High-Dimensional Predictor for Microbial Community Metabolic Profiles
Himel Mallick, Harvard; Eric Franzosa, Harvard; Lauren Mclver, Harvard; Soumya Banerjee, Harvard; Alexandra Sirota-Madi, Broad Institute; Aleksandar Kostic, Broad Institute ; Clary B. Clish, Broad Institute; Hera Vlamakis, Broad Institute; Ramnik Xavier, Broad Institute; Curtis Huttenhower, Harvard
10:50 AM
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High-Dimensional Multivariate Repeated Measures Analysis with Unequal Covariance Matrices
Xiaoli Kong, University of Kentucky; Solomon W. Harrar, University of Kentucky
10:50 AM
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Debiasing Regularized Estimators with High-Dimensional Data
Cun-Hui Zhang, Rutgers University
11:25 AM
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Sparse Clustering of High-Dimensional Gaussian Mixtures
Jing Ma, University of Pennsylvania; Tony Cai, University of Pennsylvania; Linjun Zhang, University of Pennsylvania
11:35 AM
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Semiparametric High-Dimensional Partial Linear Models: Estimation and Inference
Michael Levine, Purdue University; Lawrence D. Brown, University of Pennsylvania; Lie Wang, MIT
11:50 AM
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High-Dimensional Matrix-Variate Linear Discriminant Analysis
Aaron Molstad, University of Minnesota; Adam Rothman, University of Minnesota
11:50 AM
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