One possible escape from the Gibbard-Satterthwaite theorem is computational complexity. For example, it is NP-hard to compute if the STV rule can be manipulated. However, there is...
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...
Background: Cluster analysis has been widely applied for investigating structure in bio-molecular data. A drawback of most clustering algorithms is that they cannot automatically ...
Betweenness is a centrality measure based on shortest paths, widely used in complex network analysis. It is computationally-expensive to exactly determine betweenness; currently th...
David A. Bader, Shiva Kintali, Kamesh Madduri, Mil...
Hierarchical agglomerative clustering (HAC) is a common clustering method that outputs a dendrogram showing all N levels of agglomerations where N is the number of objects in the d...
Manoranjan Dash, Simona Petrutiu, Peter Scheuerman...