Name: 2019 Joint Statistical Meetings
Start: 2019-07-27T07:00:00+00:00
End: 2019-08-01
Location: Colorado Convention Center

Legend:
CC = Colorado Convention Center H = Hyatt Regency Denver at Colorado Convention Center
* = applied session ! = JSM meeting theme

Activity Details

		Tweet
248	Mon, 7/29/2019, 2:00 PM - 3:50 PM		CC-502
Machine Learning in Science and Industry — Contributed Papers
Section on Statistical Learning and Data Science, Text Analysis Interest Group
Chair(s): Jean Feng, University of Washington
2:05 PM	Music Classification Based on Sequential Naive Bayes and Music Score Data Tunan Ren, Guanghua School of Management; Hansheng Wang, Guanghua School of Management, Peking University, Beijing, China; Feifei Wang, School of Statistics, Renmin University of China, Beijing, China
2:20 PM	A Statistical and Machine Learning Framework for New Energy Vehicle Ride Sharing System Kaixian Yu, Didi Chuxing; Jinliang Deng, Hong Kong University of Science and Technology; Chengchun Shi, North Carolina State University; Rui Song, North Carolina State University; Qiang Yang, Hong Kong University of Science and Technology; Jieping Ye, Didi Chuxing; Hongtu Zhu, DiDi Chuxing and UNC-Chapel Hill
2:35 PM	Using Machine Learning to Assign North American Industry Classification System Codes to Establishments Based on Business Description Write-Ins Brian Dumbacher, U.S. Census Bureau; Anne Russell, U.S. Census Bureau
2:50 PM	Using a Network-Based Approach to Identify Gene Signatures That Predict Cancer Survival Minya Pu, University of California, San Diego; Judith Varner, University of California, San Diego; Karen Messer, University of California, San Diego
3:05 PM	A Machine-Learning Approach to Extract Remote-Sensing Features for Predicting Crop Yield Luca Sartore, National Institute of Statistical Sciences; Arthur Rosales, National Agricultural Statistics Service; David Johnson, National Agricultural Statistics Service; Mary Frances Dorn, Los Alamos National Laboratory; Clifford Spiegelman, Texas A&M University
3:20 PM	Dynamic Tensor Response Regression for Early Diagnosis of Alzheimer’s Disease Jie Zhou; Will Wei Sun, Purdue University; Lexin Li, University of California at Berkeley
3:35 PM	A Novel Method for Evaluating Co-Dependencies of Phenotypic Susceptibility to Multiple Antimicrobials Within and Between Bacterial Species in an Ecological Niche Heman Shakeri, Kansas State University; Victoriya Volkova, Kansas State University; Majid Jaberi-Douraki, Kansas State University

JSM 2019 Online Program

Activity Details

American Statistical Association