Abstract. In this paper, we study the problem of projected outlier detection in high dimensional data streams and propose a new technique, called Stream Projected Ouliter deTector ...
Ji Zhang, Qigang Gao, Hai H. Wang, Qing Liu, Kai X...
We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...
In this paper, a novel general purpose clustering algorithm is presented, based on the watershed algorithm. The proposed approach defines a density function on a suitable lattice,...
Manuele Bicego, Marco Cristani, Andrea Fusiello, V...
In this paper we present an innovative two-stage adaptation approach for handwriting recognition that is based on clustering of similar pages in the training data. In our approach...
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...