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350
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Tue, 7/30/2019,
10:30 AM -
12:20 PM
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CC-706
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New Methods for Time Series and Longitudinal Data — Contributed Papers
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Section on Statistical Learning and Data Science
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Chair(s): Jean De Dieu Tapsoba, Fred Hutchinson Cancer Research Center
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10:35 AM
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Regularized Estimation of VAR_X Models
Sagnik Halder
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10:50 AM
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An Efficient Two Step Algorithm for High-Dimensional Change Point Regression Models Without Grid Search
Abhishek Kaul, Washington State University; Venkata K Jandhyala, Washington State University; Stergios B Fotopoulos, Washington State University
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11:05 AM
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Joint Estimation of Structured Multivariate VAR Modeling
Peiliang Bai, University of Florida; George Michailidis, University of Florida
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11:20 AM
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Root Cause Detection Among Anomalous Time Series Using Temporal State Alignment
Sayan Chakraborty, Zillow Group Inc.
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11:35 AM
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Recurrent Neural Networks for ARMA Model Selection
Bei Chen, IBM Research; Beat Buesser, IBM Research; Kelsey DiPietro, University of Notre Dame
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11:50 AM
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Time Series Analysis with Unsupervised Learning
Meihui Guo, National Sun Yat-Sen University; Ke-Jie Chen, National Sun Yat-sen University; Cheng Han Chua, National Sun Yat-sen University
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12:05 PM
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Classification of Longitudinal Unbalanced Data: Growth Mixture Models Vs Conventional Cluster Analysis on Approximated Values at Common Time Points
Mosammat Tanbin; Benjamin E. Leiby, Thomas Jefferson University; Md Jobayer Hossain, Nemours children Healthcare Systems
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