In this paper we present new algorithms for spectral graph partitioning. Previously, the best partitioning methods were based on a combination of Combinatorial algorithms and appli...
Abstract. Motivated by the need for agent classification in sensor networking and autonomous vehicle control applications, we propose a flexible and distributed stochastic automato...
Abstract. We deal with two intimately related subjects: quasi-randomness and regular partitions. The purpose of the concept of quasi-randomness is to measure how much a given graph...
Parallel solution of irregular problems require solving the graph partitioning problem. The extended eigenproblem appears as the solution of some relaxed formulations of the graph ...
Existing graph mining algorithms typically assume that the dataset can fit into main memory. As many large graph datasets cannot satisfy this condition, truly scalable graph minin...