We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to have promising theoretical properties. In practice,...
We propose a variational bayes approach to the problem of robust estimation of gaussian mixtures from noisy input data. The proposed algorithm explicitly takes into account the un...
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...
Many current state-of-the-art speaker diarization systems exploit agglomerative hierarchical clustering (AHC) as their speaker clustering strategy, due to its simple processing str...
Huge amount of gene expression data have been generated as a result of the human genomic project. Clustering has been used extensively in mining these gene expression data to find...