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114 Mon, 8/8/2022, 8:30 AM - 10:20 AM CC-155
Time Series Methods and Applications — Contributed Papers
Section on Statistical Learning and Data Science
Chair(s): Mohamad K S Faradonbeh, University of Georgia
8:35 AM K-ARs: Fast Large-Scale Time Series Clustering
Victor Solo, UNSW Sydney
8:50 AM Recursive Partitioning for Interpretable Prescriptive Policy Making
Maria Lentini, Rowan University; Umashanger Thayasivam, Rowan University
9:05 AM A Novel Artificial Neural Network Estimator for AR(1) Time Series Parameters
Angela Folz, National Institute of Standards and Technology/University of Colorado Boulder; Mary Gregg, National Institute of Standards and Technology; Lucas Koepke, National Institute of Standards and Technology; Michael Frey, National Institute of Standards and Technology
9:20 AM A Computationally Efficient Model for Large Scale Crop Type Forecasting
Jonathon Abernethy, USDA NASS; Luca Sartore , USDA NASS; Kevin Hunt, USDA NASS; Claire Boryan, USDA NASS
9:35 AM Variational Objectives for Sequential Vartional AutoEncoders by Sequential Bayes Filtering
Tsuyoshi Ishizone, Meiji University; Tomoyuki Higuchi, Chuo University; Kazuyuki Nakamura, Meiji University
9:50 AM Near-Optimal Inference in Adaptive Linear Regression
Koulik Khamaru, University of California, Berkeley; Lester Mackey, Microsoft Research New England; Martin J. Wainwright, University of California, Berkeley; Yash Deshpande, The Voleon group
10:05 AM Time-per-Stop Forecasting in Last-Mile Deliveries
Chuchu Cheng, Amazon