Keyword Search
Legend:
CC = Baltimore Convention Center, H = Hilton Baltimore
* = applied session ! = JSM meeting theme
|
Keyword Search Criteria: Lasso returned 57 record(s)
|
|
Sunday, 07/30/2017
|
On the Asymptotic Performance of Bridge Estimators
Arian Maleki, Columbia Univ; Haolei Weng, Columbia University; Shuaiwen Wang, Columbia University
2:05 PM
|
The Biglasso Package: a Memory- and Computation-Efficient Solver for Lasso Model Fitting with Big Data in R
Yaohui Zeng, University of Iowa; Patrick Breheny, University of Iowa
2:25 PM
|
Comparing Correlated Component Regression with Lasso for Variable Selection in Logistic Regression with High-Dimensional Data
Jay Magidson, Statistical innovations
2:30 PM
|
The Generalized Lasso Problem and Uniqueness
Alnur Ali; Ryan Tibshirani, Carnegie Mellon University
2:45 PM
|
Slope Meets Lasso in Sparse Linear Regression
Pierre Bellec, Rutgers University
3:25 PM
|
On Corporate Bankruptcy Prediction
Yan Yu, University of Cincinnati; Aidong Ding, Northeastern University; Shaonan Tian, San Jose State University; Hui Guo, University of Cincinnati
4:05 PM
|
Adaptive Large-Scale Testing under Heterogeneity Sparsity
Xiang Lyu, Purdue University; Guang Cheng, Purdue
4:20 PM
|
Estimating Dynamic Brain Functional Networks Using Multi-Subject fMRI Data
Suprateek Kundu, Emory University, Rollins School of Public Health
4:25 PM
|
Combining Clinical and Nonclinical Big Data from Multiple Sources
Javier Cabrera, Rutgers University; Birol Emir, Pfizer Inc; Demissie Alemayehu, Pfizer Inc
5:25 PM
|
Multi-Resolution Functional ANOVA for Large-Scale, Many-Input Nonlinear Regression, Estimation, and Inference
Chih-Li Sung, Georgia Institute of Technology; Wenjia Wang, Georgia Institute of Technology; Matthew Plumlee, University of Michigan; Benjamin Haaland, Georgia Institute of Technology
5:35 PM
|
|
Monday, 07/31/2017
|
A Case Study in Adaptive LASSO Logistic Regression: Factors Related to Cyclist Death When Drivers Are Distracted
Lysbeth Floden, University of Arizona; Patrick Anthony O'Connor, University of Arizona; Melanie Bell, University of Arizona
|
Variable Selection for High-Dimensional Data via Generalized Penalty
Mingwei Sun, University of Alabama; Pu Patrick Wang, University of Alabama
|
Neighborhood Selection with Application to Social Networks
Nana Wang; Wolfgang Polonik, University of California, Davis
|
Multivariate logistic regression analysis for multiple-infection group testing data
Juexin Lin, University of South Carolina; Dewei Wang, University of South Carolina
|
Time Series Model Fitting and Regularization Methods
Soumendra N Lahiri, North Carolina State University
9:50 AM
|
Variable Selection for High-Dimensional Data via Generalized Penalty
Mingwei Sun, University of Alabama; Pu Patrick Wang, University of Alabama
9:55 AM
|
Neighborhood Selection with Application to Social Networks
Nana Wang; Wolfgang Polonik, University of California, Davis
10:00 AM
|
Simultaneous Variable Selection and Structural Dimension Estimation in Sufficient Dimension Reduction
Haileab Hilafu, University of Tennessee; Wenbo Wu, University of Oregon
10:55 AM
|
On Data Integration Problems with Manifolds
Kenneth Ryan, WVU; Mark Culp, West Virginia University
11:05 AM
|
ODE Reconstruction of High-Dimensional Genetic Networks Through Game Theory
Rongling Wu, Pennsylvania State University; Libo Jiang, Beijing Forestry University
11:25 AM
|
A Case Study in Adaptive LASSO Logistic Regression: Factors Related to Cyclist Death When Drivers Are Distracted
Lysbeth Floden, University of Arizona; Patrick Anthony O'Connor, University of Arizona; Melanie Bell, University of Arizona
11:40 AM
|
Group Variable Selection with Compositional Covariates
Anna Plantinga, University of Washington; Michael C. Wu, Fred Hutchinson Cancer Research Center
2:20 PM
|
Cancer Staging in Meta-Analysis by Group Fused Lasso
Wenshuo Liu, University of Wisconsin Madison; Tianjie Wang, University of Wisconsin Madison; Menggang Yu, university of wisconsin-madison
2:35 PM
|
|
Tuesday, 08/01/2017
|
Parsimonious Modeling for Kinematic Data
Md Islam, North Carolina State University; Jonathan W. Stallings, North Carolina State University
|
Evaluating the Effect of Weighting Adjustments on HIV Prevalence Estimates in Three Population-Based HIV Impact Assessments Surveys
Tien-Huan Lin, Westat; Natalia Weil, Westat; Ismael Flores Cervantes, Westat; Suzue Saito, ICAP at Columbia University
8:50 AM
|
Sparse Penalization for Non-Hierarchical Interactions
Claus Ekstrom, Biostatistics, University of Copenhagen
9:20 AM
|
An Application of High-Dimensional Multiclass Classification Methods to Listeria Monocytogenes Whole Genome Multilocus Sequence Typing Data
Sunkyung Kim, Centers for Disease Control and Prevention; Gordana Derado, Centers for Disease Control and Prevention; Anna J Blackstock, Centers for Disease Control and Prevention; Conrad Amanda, Centers for Disease Control and Prevention; Heather Carleton, Centers for Disease Control and Prevention
9:20 AM
|
Sparse Group Fused Lasso in High Dimension
David Degras, University of Massachusetts Boston
10:05 AM
|
Nonparametric Variable Screening and Preselection for Functional Data with Application to Time Course Gene Expression Profiles
Jan Gertheiss, Clausthal University of Technology
10:55 AM
|
Parsimonious Modeling for Kinematic Data
Md Islam, North Carolina State University; Jonathan W. Stallings, North Carolina State University
11:10 AM
|
A Regularized Bayesian Approach to Direct and Indirect Effects When Both Exposure and Mediator Are High-Dimensional
Yu-Bo Wang, National Institutes of Health; Zhen Chen, NICHD; Germaine M. Louis, NICHD
2:05 PM
|
A Multicollinearity-Adjusted Adaptive LASSO for Zero-Infated Count Regression
Prithish Banerjee, Wayne State University School of Medicine; Broti Garai, West Virginia University; Shrabanti Chowdhury, Wayne State University; Himel Mallick, Harvard University
2:45 PM
|
|
Wednesday, 08/02/2017
|
Regression-Enhanced Random Forests
Haozhe Zhang, Iowa State University; Dan Nettleton, Iowa State University; Zhengyuan Zhu, Iowa State University
|
Marginal False Discovery Rates for Penalized Regression Models
Patrick Breheny, University of Iowa
8:35 AM
|
Regression-Enhanced Random Forests
Haozhe Zhang, Iowa State University; Dan Nettleton, Iowa State University; Zhengyuan Zhu, Iowa State University
8:45 AM
|
A Bayesian Lasso Functional Clustering Model
Alejandro Murua, Universite de Montreal; Folly Adjogou, Université de Montréal; Wolfgang Raffelsberger, Institut de Génetique et de Biologie Moléculaire et Cellulaire, Université de Strasbourg
9:15 AM
|
Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers
Veeranjaneyulu Sadhanala, Carnegie Mellon University; Yu-Xiang Wang, Carnegie Mellon University; Ryan Tibshirani, Carnegie Mellon University
9:25 AM
|
Rare Feature Selection in High Dimensions
Xiaohan Yan, Cornell University; Jacob Bien, Cornell University
10:35 AM
|
Inflated Values Selection Method on Multiple-Inflated Poisson Model
Qiuya Li; Kwok Fai Geoffrey TSO, City University of Hong Kong; Yichen Qin, University of Cincinnati; Yang Li, Renmin University of China
10:35 AM
|
Optimal Sparse Linear Prediction for Block-Missing Multi-Modality Data Without Imputation
Guan Yu, State University of New York at Buffalo; Quefeng Li, The University of North Carolina at Chapel Hill; Dinggang Shen, The University of North Carolina at Chapel Hill; Yufeng Liu, University of North Carolina
11:15 AM
|
Variable Selection for highly correlated predictors
Fei Xue, University of Illinois at Urbana-Champaign; Annie Qu, University of Illinois at Urbana-Champaign
11:20 AM
|
Properties of Data-Dependent Variable Selection Methods
Sen Tian, New York University, Stern School of Business; Clifford M. Hurvich, New York University, Stern School of Business; Jeffrey S. Simonoff, New York University, Stern School of Business
11:20 AM
|
Variable Selection for Massive Data Using the Divide And
Lei Yang, New York University; Yixin Fang, New Jersey Institute of Technology; Junhui Wang, CityU; Yongzhao Shao, New York University-School of Medicine
11:35 AM
|
Comparing Cross Validation Methods for Penalized Cox Regression
Biyue Dai, University of Iowa; Patrick Breheny, University of Iowa
11:50 AM
|
Efficient Bounds for Best Subset Selection Using Mixed Integer Linear Programming
Ana Kenney; Francesca Chiaromonte, Penn State University; Giovanni Felici, IIASI CNR
11:50 AM
|
Empirical Bayes Methods for Penalized Regression: Estimation for Noisy Matrices/Tensors Without Replicates and Penalized Regression with Unknown Norm Penalty
Maryclare Griffin; Peter Hoff, Duke University
12:05 PM
|
Regularized Estimation in Sparse Multivariate Regression for High-Dimensional DNA Methylation Data
Lei Liu, Northwestern University; Haixiang Zhang, Tianjin University; Grace Yoon, Northwestern University; Yinan Zheng, Northwestern University; Lifang Hou, Northwestern University; Wei Zhang, Northwestern University; Andrea Baccarelli, Columbia University
2:05 PM
|
Double Robust Matching Estimators for High-Dimensional Confounding Adjustment
Joseph Antonelli; Matthew Cefalu, RAND Corporation; Nathan Palmer, Harvard Medical School; Denis Agniel, RAND Corporation
2:05 PM
|
Post-Model Selection Estimation for Regression Models with Spatial Autoregressive Errors
Tapabrata Maiti, Michigan State University; Liqian Cai, Liberty Mutual
2:35 PM
|
A New Perspective on Boosting in Linear Regression via Modern Optimization
Rahul Mazumder, Massachusetts Institute of Technology; Robert Freund, Massachusetts Institute of Technology; Paul Grigas, University of California, Berkeley
3:20 PM
|
Semiparametric Varying-Coefficient Nonlinear Regression for Interactions in Multifactor ANOVA Models with Unbalanced or Single Replications
Yumin Huang, Tunghai University
3:20 PM
|
|
Thursday, 08/03/2017
|
Beats, Rhymes, Life, and Text Analysis: Analyzing the Lyrics of a Tribe Called Quest
Clayton Barker, SAS Institute
9:05 AM
|
Comparison of Variable Selection Methods on a National Survey of Drug Use and Health
Georgiy Bobashev, RTI International; Li-Tzy Wu, Duke University
9:35 AM
|
Variable Selection and Estimation in Causal Inference Using a Bayesian Group Lasso Approach
Brandon Koch, University of Minnesota, Division of Biostatistics; Julian Wolfson, University of Minnesota, Division of Biostatistics; David Vock, University of Minnesota
9:50 AM
|
Using Lasso Regression for the Selection of Matching Variables to Analyze Crash Risk in SHRP 2 Data for a Case-Control Setting
Huizhong Guo; Linda Ng Boyle, University of Washington
10:35 AM
|
Convex Triclustering
Brian Gaines, North Carolina State University; Eric Chi, North Carolina State University; Will Wei Sun, University of Miami; Hua Zhou, University of California, Los Angeles
10:55 AM
|
Bayesian Lasso for GWAS
LiJin Joo, New York University; Cheongeun Oh, New York University
11:20 AM
|
|
|
