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: Lasso returned 75 record(s)
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Sunday, 07/31/2016
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On the Discovery and Use of Disease Risk Factors with Logistic Regression: New Prostate Cancer Risk Factors
David Booth, Kent State University; Venugopal Gopapalakrishna-Remani, The University of Texas at Tyler; Matthew Cooper, Washington University; Fiona Green, University of Manchester; Margaret Rayman, University of Surrey
2:20 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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Global-Local Shrinkage with Horseshoe Priors
Nicholas Polson, The University of Chicago
2:55 PM
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A Penalized Likelihood Approach for Heteroscedastic Linear Models
Kwame Kankam, Penn State University; James Rosenberger, Penn State University
3:05 PM
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Individualized Subgroup Variable Selection
Xiwei Tang, University of Illinois at Urbana-Champaign; Annie Qu, University of Illinois at Urbana-Champaign
3:20 PM
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Comparison of Predictive Modeling Approaches for 30-Day All-Cause Nonelective Readmission Risk
Liping Tong, Advocate Health Care; Cole Erdmann, Cerner Corporation; Marina Daldalian, Cerner Corporation; Jing Li, Cerner Corporation; Tina Esposito, Advocate Health Care
3:20 PM
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Standard Errors, Solution Paths, and Selection of Tuning Parameters for Bayesian Lassos
Sounak Chakraborty, University of Missouri - Columbia; Vivekananda Roy, Iowa State University
3:25 PM
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Interquantile Shrinkage in Additive Models
Zengyan Fan, Nanyang Technological University; Heng Lian, University of New South Wales
4:05 PM
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A Novel Group-Fused Lasso with Applications to Dynamic Brain Connectivity
David Degras, DePaul University; Martin Lindquist, The Johns Hopkins University
4:05 PM
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A Multiresolution Model for Activation and Connectivity in fMRI Data with Functional Estimation of the Haemodynamic Response
Stefano Castruccio, Newcastle University; Hernando Ombao, University of California at Irvine; Thomas Theussl, King Abdullah University of Science and Technology; Marc Genton, KAUST
4:55 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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Comparing Novel Approaches to Subgroup Analysis in Early-Phase Clinical Trials
Marius Thomas, Novartis; Björn Bornkamp, Novartis
5:20 PM
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Monday, 08/01/2016
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What Can Be Learned from the Graphical Lasso? Generalizations of the Gaussian Assumption
Po-Ling Loh, University of Pennsylvania
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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Fused Adaptive Lasso for Spatial and Temporal Quantile Function Estimation
Ying Sun, King Abdullah University of Science and Technology; Huixia Wang, The George Washington University; Montse Fuentes, North Carolina State University
9:35 AM
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Annotation Regression of Genome-Wide Association Studies with Multiple Phenotypes
Sunyoung Shin, University of Wisconsin - Madison; Sunduz Keles, University of Wisconsin - Madison
9:35 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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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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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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Model-Based Regression Clustering for High-Dimensional Data
Emilie Devijver
11:35 AM
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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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Estimation of Multi-Granger Network Causal Models
Andrey Skripnikov, University of Florida; George Michailidis, University of Florida
2:35 PM
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Forecasting Using Sparse Cointegration
Ines Wilms; Christophe Croux, KU Leuven
2:35 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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Tuesday, 08/02/2016
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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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Estimating Time-Varying Graphical Models Through a Local Group-Lasso-Type Penalty
Jilei Yang, University of California at Davis; Jie Peng, University of California at Davis
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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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GLiDeR: Doubly Robust Estimation of Causal Treatment Effects with the Group Lasso
Brandon Koch, University of Minnesota School of Public Health; David Vock, University of Minnesota School of Public Health; Julian Wolfson, University of Minnesota
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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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Learning Parameter Heterogeneity in Data Integration
Lu Tang, University of Michigan; Peter X. K. Song, University of Michigan
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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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Variable Selection in Empirical Economics: Potential Pitfalls and Solutions
Christian Hansen, The University of Chicago Booth School of Business; Esther Duflo, MIT; Victor Chernozhukov, MIT; Maddie McKelway, MIT
8:35 AM
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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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Hierarchical Sparse Modeling: A Choice of Two Regularizers
Xiaohan Yan, Cornell University; Jacob Bien, Cornell University
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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Using Bayesian Quantile Regression Model with Group LASSO to Identify Key Health Risk Assessment Variables and Evaluate Their Predictive Power in the Patient's Future Medical Costs
Hsiu-Ching Chang, BlueCross BlueShield of MI; Hyokyoung (Grace) Hong, Michigan State University; Yu Yue, Baruch College; Min Tao, BlueCross BlueShield of MI; Darline El Reda, Michigan State University
9:35 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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Risk Estimation for High-Dimensional Lasso Regression
Daniel McDonald, Indiana University; Darren Homrighausen, Colorado State University
9:50 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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Bayesian Spatial Model Selection Using Mixtures of G-Priors and Markov Random Field Priors for Identifying Gas Plumes in Hyperspectral Data
Nicole Mendoza, University of California at Santa Cruz; Abel Rodriguez, University of California at Santa Cruz
10:35 AM
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Learning Parameter Heterogeneity in Data Integration
Lu Tang, University of Michigan; Peter X. K. Song, University of Michigan
10:40 AM
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Hypothesis Testing in High Dimensions with the Lasso
Ali Shojaie, University of Washington; Sen Zhao, University of Washington
11:05 AM
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Using Machine Learning to Correct for Survey Nonresponse Bias
Curtis Signorino, University of Rochester; Antje Kirchner, University of Nebraska - Lincoln
11:15 AM
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High-Dimensional Inference for Partial Linear Models
Zhuqing Yu
11:30 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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Spatial Large-Margin Angle-Based Classifier for Multi-Category Neuroimaging Data
Leo Yu-Feng Liu, The University of North Carolina at Chapel Hill; Yufeng Liu, The University of North Carolina at Chapel Hill; Hongtu Zhu, The University of North Carolina at Chapel Hill
2:05 PM
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Lasso-Type Network Community Detection Within Latent Space
Shiwen Shen; Edsel Aldea Pena, University of South Carolina
3:20 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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On Fitting the Constrained Lasso
Brian R. Gaines, North Carolina State University; Hua Zhou, University of California at Los Angeles
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The Rise and Fall of 'The Black Mamba': Looking Back at Kobe Bryant's Career
Clayton Barker, SAS Institute
8:35 AM
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A Computationally Efficient Algorithm for Random Effects Selection in Linear Mixed Models
Mihye Ahn, University of Nevada, Reno; Helen Zhang, University of Arizona; Wenbin Lu, North Carolina State University
8:35 AM
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Robust Variable Selection Based on the Density Power Divergence Loss
Yang Li; Wenfu Xu, Renmin University of China; Yichen Qin, University of Cincinnati; Shuangge Ma, Yale University
8:50 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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Spatial Modeling of Highway Crash Risk
Matthew J. Heaton, Brigham Young University
9:00 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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Genome-Wide Association Studies Using a Penalized Moving-Window Regression
Minli Bao, University of Iowa; Kai Wang, University of Iowa
9:50 AM
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Multi-Tuning Parameter Lasso for Sample Classification
Kimberly Siegmund, University of Southern California; Jie Liu, University of Southern California; Juan Pablo Lewinger, University of Southern California
10:35 AM
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Comparisons of Statistical Methods for Determining Gene Expression Signatures to Predict Prostate Cancer Response
Dirk Moore, Rutgers School of Public Health; Qian Dong, Celgene
11:05 AM
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Resolving the Identifiability Problem with the Lasso Regularization Method in Age-Period-Cohort Analysis
Beverly Fu; Wenjiang Fu, University of Houston
11:35 AM
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Scalable Bayesian Variable Selection for Structured Data
Suprateek Kundu, Emory University; Changgee Chang, Emory University; Qi Long, Emory University
12:05 PM
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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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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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Identification of Homogeneous Areas Through Lattice-Based Spatio-Temporal Clustering
Rodrigue Ngueyep Tzoumpe, IBM Research; Huijing Jiang, IBM; YoungDeok Hwang, IBM T. J. Watson Research Center
2:20 PM
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Post-Hoc Edge Testing for the Graphical Lasso
Maxwell Jacob Grazier G'Sell, Carnegie Mellon University; William Fithian, University of California at Berkeley
2:30 PM
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Flexible Modeling of Local Dependence in Variables with a Natural Ordering
Guo Yu, Cornell University; Jacob Bien, Cornell University
2:50 PM
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Thursday, 08/04/2016
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Generalized Orthant Normal and L1-Regularized G Priors
Christopher Hans, The Ohio State University
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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Region-Wise Variable Selection with Bayesian Group Lasso
Sayan Chakraborty, Michigan State University; Tapabrata Maiti, Michigan State University
9:05 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 Comparative Study of Penalized Least Squares and Frequentist Model Averaging
Sebastian Ankargren, Uppsala University; Shaobo Jin, Uppsala University
11:05 AM
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Exact Subset Selection in Regression via Modern Optimization
Rahul Mazumder, MIT
11:15 AM
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