Keyword Search
Legend:
CC = Baltimore Convention Center, H = Hilton Baltimore
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: vector returned 24 record(s)
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Sunday, 07/30/2017
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Predicting Phenotypes from Microarrays Using Amplified, Initially Marginal, Eigenvector Regression
Lei Ding, Indiana University; Daniel J. McDonald, Indiana University
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Semiparametric, Parametric and Possibly Sparse Models for Multivariate Long-Range Dependence
Vladas Pipiras, University Od North Carolina At Chaple Hill; Stefanos Kechagias, SAS Institute; Changryong Baek, Sungkyunkwan University
3:25 PM
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Sequential Outcome-Weighted Multicategory Learning for Estimating Optimal Individualized Treatment Rules
Xuan Zhou
4:20 PM
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Integrating Multiple-Domain Rules for Disease Classi fication: With Application to Developing Criteria Sets for Mental Disorders
Christine Mauro, Columbia University; M. Katherine Shear, Columbia University; Yuanjia Wang , Columbia University
4:50 PM
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Monday, 07/31/2017
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Finite Sample Estimation in General Vector Autoregressive Processes
Mohamad Kazem Shirani Faradonbeh, University of Michigan; Ambuj Tewari, University of Michigan; George Michailidis, University of Florida
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Empirical Bayes Analysis of Relevance Vector Machines
Anand Dixit, Iowa State University; Vivekananda Roy, Iowa State University
8:50 AM
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Estimation of Sparse Vector Autoregressive Moving Averages
David S Matteson, Cornell University; Ines Wilms, KU Leuven; Jacob Bien, Cornell University
9:25 AM
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SVM-CART for Disease Classification
Evan Reynolds, University of Michigan; Mousumi Banerjee, University of Michigan; Brian Callaghan, University of Michigan
9:35 AM
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Finite Sample Estimation in General Vector Autoregressive Processes
Mohamad Kazem Shirani Faradonbeh, University of Michigan; Ambuj Tewari, University of Michigan; George Michailidis, University of Florida
9:35 AM
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There Has to Be an Easier Way: a Simple Alternative for Parameter Tuning of Supervised Learning Methods
Jill Lundell
10:35 AM
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High-Dimensional Posterior Consistency in Bayesian Vector Autoregressive Models
Satyajit Ghosh, University of Florida; Kshitij Khare, University of Florida; George Michailidis, University of Florida
3:05 PM
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Tuesday, 08/01/2017
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What's in a Vector? Major Improvements on the Horizon for R and What They Mean for You
Gabriel Becker, Genentech Research; Luke Tierney, University of Iowa
8:35 AM
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Modeling Weather-Induced Home Insurance Risks with Support Vector Machine Regression
Vyacheslav Lyubchich, University of Maryland Center for Environmental Science; Yulia R. Gel, University of Texas at Dallas; Asim Kumer Dey, University of Texas at Dallas
9:35 AM
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Bayesian Estimation of Optimal Differencing Operator in Cointegrated Systems
Anindya Roy, University of Maryland at Baltimore County; Tucker McElroy, U. S. Census Bureau
9:35 AM
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Sparse Multi-Class Vector AutoRegressive Models
Ines Wilms, KU Leuven; Christophe Croux, KU Leuven; Luca Barbaglia, KU Leuven
10:50 AM
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Limit Theorems for Eigenvectors of the Normalized Laplacian for Random Graphs
Minh Tang, Johns Hopkins University; Carey E Priebe, Johns Hopkins University
11:15 AM
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Wednesday, 08/02/2017
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Support Vector Machine with Confidence
Haomiao Meng, Binghamton University; Wenbo Wang, Binghamton University; Xingye Qiao, Binghamton University
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Zika Is Coming, and We Need Statistics
Abigail Smith; Elaine Liu, Carnegie Mellon
8:35 AM
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Support Vector Machine with Confidence
Haomiao Meng, Binghamton University; Wenbo Wang, Binghamton University; Xingye Qiao, Binghamton University
9:00 AM
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Approximate Confidence Regions for Consensus Mean Vector in Heteroscedastic Multivariate One-Way Random Model
Jian Zhao, The EMMES Corporation
10:05 AM
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Sparse Concordance-Assisted Learning for Optimal Treatment Decision
Shuhan Liang, North Carolina State University; Wenbin Lu, North Carolina State University; Rui Song, NC State University; Lan Wang, University of Minnesota
10:35 AM
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Regret Bounds for Adaptive Control of Linear Quadratic Systems
Mohamad Kazem Shirani Faradonbeh, University of Michigan; Ambuj Tewari, University of Michigan; George Michailidis, University of Florida
11:25 AM
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Cepstral Models: An Overview of Recent Advances
Scott H. Holan, University of Missouri
2:30 PM
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A One-Class Convex Hull Peeling Method for Outlier Detection
Waldyn Martinez, Miami University; Maria L. Weese, Miami University; Allison Jones-Farmer, Miami University
3:35 PM
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