We study a number of open issues in spectral clustering: (i) Selecting the appropriate scale of analysis, (ii) Handling multi-scale data, (iii) Clustering with irregular backgroun...
—Due to adverse aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In...
In the paper, we present a new approach to multi-way Blind Source Separation (BSS) and corresponding 3D tensor factorization that has many potential applications in neuroscience an...
Andrzej Cichocki, Anh Huy Phan, Rafal Zdunek, Liqi...
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
We propose an approximate computation technique for inter-object distances for binary data sets. Our approach is based on the locality sensitive hashing, scales up with the number ...