MiLeTS 2015 - Workshop on Mining and Learning from Time Series (MiLeTS)

The inaugural MiLeTS workshop invites submission of manuscripts describing research on time series analysis and mining. Topics of interest include but are not limited to:
Time series pattern mining and detection, representation, searching and indexing, classification, clustering, prediction, forecasting, and rule mining.
BIG time series data.
Hardware acceleration techniques using GPUs, FPGAs and special processors.
Online, high-speed learning and mining from streaming time series.
Uncertain time series mining.
Privacy preserving time series mining and learning.
Time series that are multivariate, high-dimensional, heterogeneous, etc., or that possess other atypical properties.
Time series with special structure: spatiotemporal (e.g., wind patterns at different locations), relational (e.g., patients with similar diseases), hierarchical, etc.
Time series with sparse or irregular sampling, non-random missing values, and special types of measurement noise or bias.
Time series analysis using less traditional approaches, such as deep learning and subspace clustering.
Applications to high impact or relatively new time series domains, such as health and medicine, road traffic, and air quality.
New, open, or unsolved problems in time series analysis and mining (see note below).