In this paper we study the problem of constructing accurate decision tree models from data streams. Data streams are incremental tasks that require incremental, online, and any-ti...
In this work we investigate how the compiler technique of message strip mining performs in practice on contemporary high performance networks. Message strip mining attempts to redu...
This paper focuses on the detection of objects with a Lambertian surface under varying illumination and pose. We offer to apply a novel detection method that proceeds by modeling ...
Analyzing data to find trends, correlations, and stable patterns is an important task in many industrial applications. This paper proposes a new technique based on parallel coordi...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
—In this paper, we proposed a reduced polynomial neural swarm net (RPNSN) for the task of classification. Classification task is one of the most studied tasks of data mining. In ...