Time series data is prevalent in important applications such as robotics, finance, healthcare, and cloud monitoring. In these applications, we typically encounter time series with very high dimensions where the ML task is to perform classification for signal characterization, regression for prediction, or function approximation within a reinforcement learning agent.

Despite the great number of important applications with time series data, the literature of ML is not as plentiful for this input type. Additionally, the majority of ML algorithms have the underlying assumption that the samples are independent and identically distributed (iid) — which is not the case for most…