Abstract is missing.
- High quality graph partitioningPeter Sanders, Christian Schulz. 1-18 [doi]
- Abusing a hypergraph partitioner for unweighted graph partitioningBas Fagginger Auer, Rob H. Bisseling. 19-36 [doi]
- Parallel partitioning with Zoltan: Is hypergraph partitioning worth it?Sivasankaran Rajamanickam, Erik G. Boman. 37-52 [doi]
- UMPa: A multi-objective, multi-level partitioner for communication minimizationÜmit V. Çatalyürek, Mehmet Deveci, Kamer Kaya, Bora Uçar. 53-66 [doi]
- Shape optimizing load balancing for MPI-parallel adaptive numerical simulationsHenning Meyerhenke. 67-82 [doi]
- Graph partitioning for scalable distributed graph computationsAydin Buluç, Kamesh Madduri. 83-102 [doi]
- Using graph partitioning for efficient network modularity optimizationHristo Djidjev, Melih Onus. 103-112 [doi]
- Modularity maximization in networks by variable neighborhood searchDaniel Aloise, Gilles Caporossi, Pierre Hansen, Leo Liberti, Sylvain Perron, Manuel Ruiz. 113-128 [doi]
- Network clustering via clique relaxations: A community based approachAnurag Verma, Sergiy Butenko. 129-140 [doi]
- Identifying base clusters and their application to maximizing modularitySriram Srinivasan, Tanmoy Chakraborty 0002, Sanjukta Bhowmick. 141-156 [doi]
- Complete hierarchical cut-clustering: A case study on expansion and modularityMichael Hamann, Tanja Hartmann, Dorothea Wagner. 157-170 [doi]
- A partitioning-based divisive clustering technique for maximizing the modularityÜmit V. Çatalyürek, Kamer Kaya, Johannes Langguth, Bora Uçar. 171-186 [doi]
- An ensemble learning strategy for graph clusteringMichael Ovelgönne, Andreas Geyer-Schulz. 187-206 [doi]
- Parallel community detection for massive graphsE. Jason Riedy, Henning Meyerhenke, David Ediger, David A. Bader. 207-222 [doi]
- Graph coarsening and clustering on the GPUBas Fagginger Auer, Rob H. Bisseling. 223 [doi]