We consider the problem of representing graphs compactly while supporting queries efficiently. In particular we describe a data structure for representing n-vertex unlabeled graph...
Many real-world graphs have been shown to be scale-free— vertex degrees follow power law distributions, vertices tend to cluster, and the average length of all shortest paths is...
Spectral Graph Transducer(SGT) is one of the superior graph-based transductive learning methods for classification. As for the Spectral Graph Transducer algorithm, a good graph re...
A variety of computation models have been developed using graphs and graph transformations. These include models for sequential, distributed, parallel or mobile computation. A grap...
We formulate weighted graph clustering as a prediction problem1 : given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. ...