Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Background: Cluster analysis has been widely applied for investigating structure in bio-molecular data. A drawback of most clustering algorithms is that they cannot automatically ...
This paper is concerned with the problem of recovering an unknown matrix from a small fraction of its entries. This is known as the matrix completion problem, and comes up in a gr...
We describe a decentralized, adaptive mechanism for replica location in wide-area distributed systems. Unlike traditional, hierarchical (e.g, DNS) and more recent (e.g., CAN, Chor...
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....