Keyword Search
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: sparse returned 77 record(s)
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Sunday, 07/31/2016
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Integrative Analysis of Transcriptomic and Metabolomic Data via Sparse Canonical Correlation Analysis with Incorporation of Biological Information
Sandra Safo, Emory University; Qi Long, Emory University
2:05 PM
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A Power Study of the GFfit Statistic as a Lack-of-Fit Diagnostic for Sparse Two-Way Subtables
Junfei Zhu, ASU; Mark Reiser, Arizona State University; Silvia Cagnone, University of Bologna
2:05 PM
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The PICASSO Package for High Dimensions Nonconvex Sparse Learning in R
Xingguo Li; Tuo Zhao, The Johns Hopkins University; Tong Zhang, Rutgers University; Han Liu, Princeton
2:25 PM
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Integrative Sparse K-Means for Disease Subtype Discovery
George Tseng, University of Pittsburgh; Zhiguang Huo, University of Pittsburgh
2:30 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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Sparse Signal Detection in the Presence of Rare Variants and Binary Phenotype
Sixing Chen, Harvard; Xihong Lin, Harvard T.H. Chan School of Public Health
3:05 PM
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Using L_1 Data Depth Unsupervised Classifier for Detecting Communities in Networks
Yahui Tian; Yulia R. Gel, The University of Texas at Dallas
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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Overlapping Community Detection in Networks via Sparse Principal Component Analysis
Jesus Daniel Arroyo Relion, University of Michigan; Elizaveta Levina, University of Michigan
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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Monday, 08/01/2016
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Period Estimation for Sparsely Sampled Quasi-Periodic Functions: Application to Mira Variable Stars
Shiyuan He, Texas A&M University
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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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Sparse Regression for Block Missing Data Without Imputation
Yufeng Liu, The University of North Carolina at Chapel Hill
8:35 AM
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Fast Covariance Estimation for Sparse Functional Data
Cai Li, North Carolina State University; Luo Xiao, North Carolina State University; William Checkley, The Johns Hopkins University; Ciprian Crainiceanu, The Johns Hopkins University
8:35 AM
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Sparse Spatial Dynamic Factor Model with Basis Expansion
Takamitsu Araki; Shotaro Akaho, National Institute of Advanced Industrial Science and Technology
8:50 AM
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Genomic Determination Index
Cheng Cheng, St. Jude Children's Research Hospital; Robert J. Autry, St. Jude Children's Research Hospital; Wenjian Yang, St. Jude Children's Research Hospital; Steven Paugh, St. Jude Children's Research Hospital; William E. Evans, St. Jude Children's Research Hospital
8:50 AM
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Introduction to the TextmineR Package for R
Thomas Jones, Impact Research
9:05 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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Period Estimation for Sparsely Sampled Quasi-Periodic Functions: Application to Mira Variable Stars
Shiyuan He, Texas A&M University
9:30 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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A Nonparametric Bayesian Approach for Sparse Sequence Estimation
Yunbo Ouyang, University of Illinois at Urbana-Champaign; Feng Liang, University of Illinois at Urbana-Champaign
9:50 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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Why Popular Bayesian Nonparametric Methods Fail for Sparse Clustering Tasks
Rebecca Steorts, Duke University; Jeffrey Miller, Duke University; Brenda Betancourt; Abbas Zaidi, Duke University; Hanna Wallach, University of Massachusetts - Amherst/Microsoft Research
10:35 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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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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Bayesian Variable Selection: An Alternative Route to Hierarchical Gene-Environment Interactions
Cen Wu, Kansas State University; Yu Jiang, University of Memphis; Jinfeng Wei, Maryville University; Shuangge Ma, Yale University
11:35 AM
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A Two-Stage Approach to Analysis of Health Effects of Environmental Chemical Mixtures: Informed Sparse Principal Component Analysis Followed by Segmented Regression
Roman Jandarov, University of Cincinnati; Susan Pinney, University of Cincinnati; Liang Niu, University of Cincinnati
11:50 AM
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Sparse Latent Class Regression for Multivariate Binary Data: A Bayesian Approach
Zhenke Wu, The Johns Hopkins University; Scott L. Zeger, The Johns Hopkins University
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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Sparse Opportunistic Sampling in Population Pharmacokinetic Studies
William H. Fissell, Vanderbilt University; Pratish Patel, Vanderbilt University; Matthew S. Shotwell, Vanderbilt University
2:05 PM
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Optimal Design for Sampling Functional Data
So-Young Park, North Carolina State University; Luo Xiao, North Carolina State University; Jayson Wilbur, Metrum Research Group; Ana-Maria Staicu, North Carolina State University
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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Time Series Model Selection via Adpative Sparse Estimation
Seong-Tae Kim, North Carolina A&T State University; Kendra Kirby, North Carolina A&T State University
2:20 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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Forecasting Using Sparse Cointegration
Ines Wilms; Christophe Croux, KU Leuven
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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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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Sparse Predictive Modeling for Bank Telemarketing Success Using Smooth-Threshold Estimating Equations
Yoshinori Kawasaki, Institute of Statistical Mathematics; Masao Ueki, Kurume University
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Group Discrimination Using Sparse Network Modeling of Resting-State fMRI
Maria Puhl, University of Tulsa; William Coberly, University of Tulsa; Alejandro Hernandez, University of Tulsa; Kyle Simmons, Laureate Institute for Brain Research
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Bioequivalence Test of AUC for Sparse Crossover Design
Guoying Sun, FDA/CDER; Huaixiang Li, FDA/CDER; Fairouz Makhlouf, FDA/CDER; Donald Schuirmann, FDA/CDER; Stella Grosser, FDA/CDER
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Fish Cliques: Evidence of Social Groups from Sparse Observations in Time and Space
Jean Adams, USGS Great Lakes Science Center; Stephen Riley, USGS Great Lakes Science Center; Charles Krueger, Michigan State University; Tom Binder, USGS Great Lakes Science Center; Taaja Tucker, USGS Great Lakes Science Center
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Penalized Principal Logistic Regression for Sparse Sufficient Dimension Reduction
Seung Jun Shin, Korea University; Andreas Artemiou, Cardiff University
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The Knockoff Filter for FDR Control in Group-Sparse and Multitask Regression
Ran Dai, The University of Chicago; Rina Foygel Barber, The University of Chicago
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Hierarchical Sparse Modeling: A Choice of Two Regularizers
Xiaohan Yan, Cornell University; Jacob Bien, Cornell University
8:50 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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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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Sparse Additive Graphical Models
Hyonho Chun, Purdue University; Ji Hwan Oh, Purdue University
9:35 AM
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Surrogate Aided Unsupervised Recovery of Sparse Signals in Single Index Models for Binary Outcomes Using Extreme Sampling
Abhishek Chakrabortty, Harvard; Tianxi Cai, Harvard
9:50 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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Sparse Multidimensional Graphical Models: A Unified Bayesian Framework
Yang Ni; Francesco Stingo, MD Anderson Cancer Center; Veera Baladandayuthapani, MD Anderson Cancer Center
11:35 AM
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Penalized Principal Logistic Regression for Sparse Sufficient Dimension Reduction
Seung Jun Shin, Korea University; Andreas Artemiou, Cardiff University
11:35 AM
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Joint Modeling of Noncommensurate Sparse Functional Predictors with an Application to Ecological Momentary Assessment (EMA) Data
Jaroslaw Harezlak, Indiana University Fairbanks School of Public Health; Fei He, Indiana University Fairbanks School of Public Health; Armando Teixeira-Pinto, University of Sydney
11:35 AM
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Fish Cliques: Evidence of Social Groups from Sparse Observations in Time and Space
Jean Adams, USGS Great Lakes Science Center; Stephen Riley, USGS Great Lakes Science Center; Charles Krueger, Michigan State University; Tom Binder, USGS Great Lakes Science Center; Taaja Tucker, USGS Great Lakes Science Center
11:45 AM
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The Knockoff Filter for FDR Control in Group-Sparse and Multitask Regression
Ran Dai, The University of Chicago; Rina Foygel Barber, The University of Chicago
11:50 AM
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Oracle Inequalities for Network Models and Sparse Graphon Estimation
Alexandre Tsybakov, ENSAE; Olga Klopp, University Paris 10/CREST; Nicolas Verzelen, INRA
2:05 PM
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Sparse Motifs: Discovering Structure in Massive Graphs
Zehang Li, University of Washington; Tyler McCormick, University of Washington; Joshua Blumenstock, University of Washington
2:20 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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Optimal Designs for Longitudinal Studies via Functional Data Analysis
Hao Ji, University of California at Davis; Hans-Georg Mueller, University of California at Davis
3:05 PM
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Functional Data Analysis for Sparse and Irregular Longitudinal MRI Measurements in the Developing Brain
Xiongtao Dai, Healthy Birth, Growth and Development knowledge integration (HBGDki) Community; Hans-Georg Mueller, University of California at Davis; Jane-Ling Wang, University of California at Davis
3:25 PM
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Wednesday, 08/03/2016
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Bayesian Inference in Nonparanormal Graphical Models
Jami Jackson, North Carolina State University; Subhashis Ghosal, North Carolina State University
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Sparse, Efficient Phylogenetic Factor Analysis
Max Tolkoff; Marc Adam Suchard, University of California at Los Angeles
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Incorporating Biological Information in Sparse Principal Component Analysis with Application to Genomic Data
Ziyi Li, Emory University; Qi Long, Emory University; Sandra Safo, Emory University
8:35 AM
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Sparse Seasonal and Periodic Vector Autoregressive Modeling
Vladas Pipiras, The University of North Carolina at Chapel Hill; Changryong Baek, Sungkyunkwan University; Richard A. Davis, Columbia University
8:55 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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A New Class of Nonseparable Bayesian Hierarchical Spatial Modeling for Sparse Gaussian Processes
Bledar Konomi, University of Cincinnati
9:20 AM
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Unified Inference for Sparse and Dense Longitudinal Data in Time-Varying Coefficient Models
Yixin Chen, Sanofi; Weixin Yao, University of California at Riverside
9:50 AM
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Sparse, Efficient Phylogenetic Factor Analysis
Max Tolkoff; Marc Adam Suchard, University of California at Los Angeles
9:55 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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Reduced Sample-Compressed Learning of Big Probability Distributions
Subhadeep Mukhopadhyay, Temple University Fox School of Business
11:05 AM
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Edge Exchangeability: A New Foundation for Modeling Network Data
Harry Crane, Rutgers University; Walter Dempsey, University of Michigan
12:05 PM
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Union of Intersections (UoI) Method for Bootstrap-Based Interpretable Discovery
Sharmodeep Bhattacharyya, Oregon State University; Kristofer Bouchard, Lawrence Berkeley National Laboratory; Michael W. Mahoney, University of California at Berkeley; Farbod Roosta-Khorasani, University of California at Berkeley; Alejandro F. Bujan, University of California at Berkeley
2:05 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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Thursday, 08/04/2016
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Clustering with Non-Convex Penalized Gaussian Graphical Models for Simultaneous Parameter Estimation and Pursuit of Sparseness
Chen Gao, University of Minnesota; Wei Pan, University of Minnesota; Xiaotong Shen, University of Minnesota; Yunzhang Zhu, The Ohio State University
9:05 AM
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Exact Subset Selection in Regression via Modern Optimization
Rahul Mazumder, MIT
11:15 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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Pathwise Coordinate Optimization for Nonconvex Sparse Learning: Algorithm and Theory
Tuo Zhao, The Johns Hopkins University; Han Liu, Princeton; Tong Zhang, Rutgers University
12:05 PM
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Sparse Mean-Variance Portfolios: A Penalized Utility Approach
David Puelz, The University of Texas; Carlos Carvalho, The University of Texas; P. Richard Hahn, The University of Chicago Booth School of Business
12:05 PM
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