Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
Data access prediction has been proposed as a mechanism to overcome latency lag, and more recently as a means of conserving energy in mobile systems. We present a fully adaptive p...
James Larkby-Lahet, Ganesh Santhanakrishnan, Ahmed...
Abstract. This text is an informal review of several randomized algorithms that have appeared over the past two decades and have proved instrumental in extracting efficiently quant...
There has been an explosion of hyperlinked data in many domains, e.g., the biological Web. Expressive query languages and effective ranking techniques are required to convert this...
Graphs are widely used to model real world objects and their relationships, and large graph datasets are common in many application domains. To understand the underlying character...
Yuanyuan Tian, Richard A. Hankins, Jignesh M. Pate...