A fundamental task of data analysis is comprehending what distinguishes clusters found within the data. We present the problem of mining distinguishing sets which seeks to find s...
— The problem of appearance-based mapping and navigation in outdoor environments is far from trivial. In this paper, an appearance-based topological map, covering a large, mixed ...
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
We present a parallel version of BIRCH with the objective of enhancing the scalability without compromising on the quality of clustering. The incoming data is distributed in a cyc...
Clustering is an important function in data mining. Its typical application includes the analysis of consumer's materials. Adaptive resonance theory network (ART) is very pop...