Matthew Gibson-Lopez

Curves as input data naturally arise in a variety of fields including finance, seismology, medicine, spatio-temporal data mining, malicious activity detection, and more. A common way to analyze these data sets is similarity matching, for which we need metrics that measure the similarity between curves. I will explore the Continuous Dynamic Time Warping (CDTW) distance: how it improves on previous, more common metrics; existing algorithms for computing it exactly or approximatively for various cases; and finally our own novel algorithm for approximating it between piecewise algebraic curves.