—Algorithmic enhancements are described that enable large computational reduction in mean square-error data clustering. These improvements are incorporated into a parallel data-c...
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
We present a document-specific OCR system and apply it to a corpus of faxed business letters. Unsupervised classification of the segmented character bitmaps on each page, using a ...
EM algorithm is an important unsupervised clustering algorithm, but the algorithm has several limitations. In this paper, we propose a fast EM algorithm (FEMA) to address the limi...
We propose a hierarchical, unsupervised clustering algorithm (TreeGCS) based upon the Growing Cell Structure (GCS) neural network of Fritzke. Our algorithm improves an inconsisten...