Relational data appear frequently in many machine learning applications. Relational data consist of the pairwise relations (similarities or dissimilarities) between each pair of i...
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip...
Abstract—Despite recent efforts to characterize complex networks such as citation graphs or online social networks (OSNs), little attention has been given to developing tools tha...
Bruno F. Ribeiro, Pinghui Wang, Fabricio Murai, Do...
Graph theory provides a powerful set of metrics and conceptual ideas to model and investigate the behavior of communication networks. Most graph-theoretical frameworks in the netw...
We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is co...
Graph drawing and visualization represent structural information ams of abstract graphs and networks. An important subset of graphs is directed acyclic graphs (DAGs). E-Spring alg...