Clustering can be defined as a data assignment problem where the goal is to partition the data into nonhierarchical groups of items. In our previous work, we suggested an informati...
We propose a novel patch-based image representation that is useful because it (1) inherently detects regions with repetitive structure at multiple scales and (2) yields a paramete...
Lena Gorelick, Andrew Delong, Olga Veksler, Yuri B...
This paper presents an asymptotic analysis of the eigen value decomposition (EVD) of the sample covariance matrix associated with independent identically distributed (IID) non nec...
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stopp...
Abstract. Integrative mining of heterogeneous data is one of the major challenges for data mining in the next decade. We address the problem of integrative clustering of data with ...