Most existing work uses dual decomposition and subgradient methods to solve Network Utility Maximization (NUM) problems in a distributed manner, which suffer from slow rate of con...
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
Texture information in images is coupled with geometric macrostructures and piecewise-smooth intensity variations. Decomposing an image f into a geometric structure component u an...
Wedescribea novel approachfor clustering collectionsof sets,andits applicationto theanalysis and mining of categoricaldata. By "categorical data," we meantableswith fiel...
David Gibson, Jon M. Kleinberg, Prabhakar Raghavan