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CC = Baltimore Convention Center,    H = Hilton Baltimore
* = applied session       ! = JSM meeting theme

Activity Details

175 Mon, 7/31/2017, 10:30 AM - 12:20 PM CC-Halls A&B
Contributed Poster Presentations: Section on Statistical Learning and Data Science — Contributed Poster Presentations
Section on Statistical Learning and Data Science
Chair(s): Jessi Cisewski, Yale University
1: Mixture DOE Approach for Weights Optimization in Regression Ensembles — Stanislav Zakharkin, PepsiCo
2: Gaussian Mixture Models as Automated Particle Classifiers for Fast Neutron Detectors — Brenton Blair, Lawrence Livermore National Laboratory ; Ron Wurtz, Lawrence Livermore National Laboratory
3: Model-Based Clustering with Application of Copula for Symbolic Data — Wenhao Pan, University of Georgia ; lynne Billard, University of Georgia
4: Identifying clusters of cognitive functioning trajectories in elderly: A comparison of three methodologies — Victor Talisa, Department of Biostatistics, University of Pittsburgh ; Tianxiu Wang, University of Pittsburgh ; Zhongying Xu, University of Pittsburgh ; Joyce Chang, University of Pittsburgh
6: Detecting Local Closeness of Two Distribution Functions — Zhun Deng, Harvard ; Jie Ding, Harvard ; Vahid Tarokh, Harvard
8: Batch Policy Evaluation for Average Reward — Peng Liao ; Susan A Murphy, University of Michigan
9: Optimal Variable Selection in Regression Models — Jie Ding, Harvard ; Vahid Tarokh, Harvard ; Yuhong Yang, University of Minnesota
10: Variable Selection and Penalized Regression Methods for Clinical Projects: Practical Issues — Anne Eaton ; Mithat Gönen, Memorial Sloan Kettering Cancer Center
11: AN ANALYSIS of NETWORK DISCUSSION TRENDS in TWITTER USING HASHTAG CLUSTERS — Elizabeth Tigner, Purdue University ; Jennifer Neville, Purdue University
12: Periodicity in Game Theory — Michael Alexander Smith, Purdue University ; Bret Benesh, The College of St. Benedict/St. John's University ; Jamylle Carter, Diablo Valley College ; Deidra A. Coleman, Philander Smith College ; Jack Good, Purdue University ; Jennifer Travis, Lone Star College-North Harris ; Mark Ward, Purdue University
13: Using Statistical Learning to Develop a More Sensitive Outcome for Progressive Multiple Sclerosis — Christopher Barbour, Montana State University ; Mark Greenwood, Montana State University ; Peter Kosa, National Institute of Neurological Disorders and Stroke, National Institutes of Health ; Danish Ghazali, National Institute of Neurological Disorders and Stroke, National Institutes of Health ; Makoto Tanigawa, National Institute of Neurological Disorders and Stroke, National Institutes of Health ; Blake Snyder, National Institute of Neurological Disorders and Stroke, National Institutes of Health ; Bibiana Bielekova, National Institute of Neurological Disorders and Stroke, National Institutes of Health
15: CAM2 Network Camera Object Detection Dataset and Analysis — Kent Gauen, Purdue University ; Yuxiang Zi, Purdue University ; John Laiman, Purdue University ; Nirmal Asokan, Purdue University ; Yung-Hsiang Lu, Purdue University
16: Optimization and Testing in Generalized Independent Component Analysis — Ze Jin, Cornell University ; David S Matteson, Cornell University
17: Sequential Graph Matching and Streaming Sequential Monte Carlo — Seong-Hwan Jun
18: Spline Density Estimation and Inference with Model-Based Penalties — Jian Shi, University of California, Santa Barbara
19: Accelerated Failure Time Model with Log-Concave Error Distribution — Sunyul Kim, Sungkyunkwan university statstics department ; Byung tae Seo, Sungkyunkwan University
 
 
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