Theoretically and Practically Efficient Parallel Nucleus Decomposition

von Shi, Jessica
Veröffentlicht in International Conference on Very Large Data Bases (48. : 2022 : Sydney; Online) 48th International Conference on Very Large Data Bases (VLDB 2022) ; Part 1 of 6 (2023)

ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms

von Dhulipala, Laxman
Veröffentlicht in VLDB (47. : 2021 : Kopenhagen; Online) 47th International Conference on Very Large Data Bases 2021 ; Part 1 of 4 (2021)

Parallel Batch-Dynamic k-Clique Counting

von Dhulipala, Laxman
Veröffentlicht in SIAM Symposium on Algorithmic Principles of Computer Systems (2. : 2021 : Online) Symposium on Algorithmic Principles of Computer Systems (APOCS21) (2021)

Scalable Community Detection via Parallel Correlation Clustering

von Shi, Jessica
Veröffentlicht in VLDB (47. : 2021 : Kopenhagen; Online) 47th International Conference on Very Large Data Bases 2021 ; Part 3 of 4 (2021)

Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth

von Dhulipala, Laxman
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 30 of 50 (2023)

ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain

von Yu, Shangdi
Veröffentlicht in International Conference on Very Large Data Bases (48. : 2022 : Sydney; Online) 48th International Conference on Very Large Data Bases (VLDB 2022) ; Part 1 of 6 (2023)

HIERARCHICAL AGGLOMERATIVE GRAPH CLUSTERING IN NEARLY-LINEAR TIME

von DHULIPALA, LAXMAN
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 4 of 16 (2022)

Sage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs

von Dhulipala, Laxman
Veröffentlicht in VLDB (46. : 2020 : Online) 46th International Conference on Very Large Data Bases ; Volume 3 of 5 (2020)