Short Bio
Geoff Webb is Research Director of the Monash University Data Futures Institute. He is a data science consultant and a technical advisor to data science startups BigML and FROOMLE. He has been Editor in Chief of the premier data mining journal, Data Mining and Knowledge Discovery (2005 to 2014) and Program Committee Chair of the two top data mining conferences, ACM SIGKDD (2015) and IEEE ICDM (2010), as well as General Chair of ICDM (2012). His primary research areas are machine learning, data mining and computational structural biology. Many of his learning algorithms are included in the widely-used BigML, R and Weka machine learning workbenches. He is an IEEE Fellow and his many awards include the inaugural Eureka Prize for Excellence in Data Science in 2017.
Abstract
Time series classification is a fundamental data science task, 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-the-art developments, but with many orders of magnitude greater efficiency and scalability. These make time series classification feasible at hitherto unattainable scale.