MiLeTS'21: 7th KDD Workshop on Mining and Learning from Time Series

Abstract

Time series data are ubiquitous. Rapid advances in diverse sensing technologies, ranging from remote sensors to wearables and social sensing, are generating a rapid growth in the size and complexity of time series archives. This has resulted in a fundamental shift away from parsimonious, infrequent measurement to nearly continuous monitoring and recording. This demands development of new tools and solutions. The goals of this workshop are to: (1) highlight the significant challenges that underpin learning and mining from time series data (e.g. irregular sampling, spatiotemporal structure, and uncertainty quantification), (2) discuss recent algorithmic, theoretical, statistical, or systems-based developments for tackling these problems, and (3) synergize the research activities and discuss both new and open problems in time series analysis and mining.