Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
When monitoring sensory data (e.g., from a wearable device) the context oftentimes changes abruptly: people move from one situation (e.g., working quietly in their office) to ano...
In this paper, we propose a novel approach to address the problem of change detection in time series data. Our approach is based on wavelet footprints proposed originally by the si...
In this paper, we study the problem of anomaly detection in high-dimensional network streams. We have developed a new technique, called Stream Projected Ouliter deTector (SPOT), t...