We present a general approach for designing approximation algorithms for a fundamental class of geometric clustering problems in arbitrary dimensions. More specifically, our appro...
Wenceslas Fernandez de la Vega, Marek Karpinski, C...
This paper discusses the topic of dimensionality reduction for k-means clustering. We prove that any set of n points in d dimensions (rows in a matrix A ∈ Rn×d ) can be project...
Clock skew scheduling has been effectively used to reduce the clock period of sequential circuits. However, this technique may become impractical if a different skew must be appli...
We propose a scalable technique called Seeded Clustering that allows us to maintain R-tree indices by bulk insertion while keeping pace with high data arrival rates. Our approach ...
This paper presents results of a study of the effect of global variables on the quantity of dependence in general and on the presence of dependence clusters in particular. The pa...
David Binkley, Mark Harman, Youssef Hassoun, Syed ...