Time series data is ubiquitous. In domains as diverse as finance, entertainment, transportation and health-care, we observe a fundamental shift away from parsimonious, infrequent measurement to nearly continuous monitoring and recording. 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. Thus, although time series analysis has been studied extensively, its importance only continues to grow. Furthermore, modern time series data pose significant challenges to existing techniques both in terms of the structure (e.g., irregular sampling in hospital records and spatiotemporal structure in climate data) and size. These challenges are compounded by the fact that standard i.i.d. assumptions used in other areas of machine learning are not appropriate for time series and new theory, models and algorithms are needed to process and analyse this data.

The goal of this workshop is to bring together theoretical and applied researchers interested in the analysis of time series and development of new algorithms to process sequential data. This includes algorithms for time series prediction, classification, clustering, anomaly and change point detection, correlation discovery, dimensionality reduction as well as a general theory for learning and comparing stochastic processes. We invite researchers from the related areas of batch and online learning, reinforcement learning, data analysis and statistics, econometrics, and many others to contribute to this workshop.

Our workshop will build on the success of past two time series workshops that were held at NIPS and KDD (also co-organized by the proposers). The workshop will attract a broader audience from ICML community. In particular, when we have the KDD workshop on time series in 2015 held in Sydney, it attracts many local researchers in Australia who work on time series research or related applications. We expect the proposed workshop will be a hit given its large interest in the ICML community as well as the local interest in Sydney.