We propose a framework, called MIC, which adopts an information-theoretic approach to address the problem of quantitative association rule mining. In our MIC framework, we first d...
We propose a flexible summarization framework for teamsport videos, which is able to integrate both the knowledge about displayed content (e.g. level of interest, type of view, et...
We present a framework for passivity-preserving model reduction for RLC systems that includes, as a special case, the well-known PRIMA model reduction algorithm. This framework pr...
In this paper, a cluster-based framework is introduced for comparing analysis methods of functional magnetic resonance images (fMRI). In the proposed framework, fMRI data is repla...