Time Series Classification at Scale

Time series classification is a fundamental data science problem, providing understanding of dynamic processes as they evolve over time. The recent introduction of ensemble techniques has revolutionised this field, greatly increasing accuracy, but at a cost of increasing already burdensome computational overheads. I present new time series classification technologies that achieve the same accuracy as recent state-of-theart developments, but with many orders of magnitude greater efficiency and scalability. These make time series classification feasible at hitherto unattainable scale. Copyright © 2020 by the paper’s authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).