14th IEEE ICMLA 2015 – This paper discusses how we should think about anomaly detection for streaming applications. It introduces a new open-source benchmark for detecting anomalies in real-time, time-series data.
Recently there has been much interest in building custom hardware implementations of HTM systems. This paper discusses one such scenario, and shows how to port HTM algorithms to analog hardware platforms such as the one developed by the Human Brain Project.
An earlier version of the above submission, this paper applies our mathematical model of sparse representations to practical HTM systems.
There have been changes in our thinking, in algorithm implementation, in terminology and in other areas since the HTM whitepaper was written, rendering part of this paper obsolete. Much of this paper has been replaced by BAMI and the current white papers.
