Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Typical clustering algorithms output a single clustering of the data. However, in real world applications, data can often be interpreted in many different ways; data can have diff...
Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...
High-dimensional data visualization is receiving increasing interest because of the growing abundance of highdimensional datasets. To understand such datasets, visualization of th...
In this paper, it is shown that Independent Component Analysis (ICA) of sparse signals (sparse ICA) can be seen as a cluster-wise Principal Component Analysis (PCA). Consequently,...
Massoud Babaie-Zadeh, Christian Jutten, Ali Mansou...