Regime switching models, in which the state of the world is locally stationary, are a useful abstraction for many continuous valued data streams. In this paper we develop an onlin...
Gordon J. Ross, Dimitris K. Tasoulis, Niall M. Ada...
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Abstract. We propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection in unlabeled audit data streams. The framework owns a...
Abstract Current, data-driven applications have become more dynamic in nature, with the need to respond to events generated from distributed sources or to react to information extr...