Publications
Papers
- - Michael Greenbaum, Ke Fan, Sidhartha Kumar, Guimu Guo, "Accelerating Maximal Quasi-Clique Mining using GPUs", in preparation .
Posters
- - Michael Greenbaum, Ke Fan, Sidhartha Kumar, Guimu Guo, "Accelerating Maximal Quasi-Clique Mining using GPUs", to be presented at SURP Research Symposium 2024, (2024).
- - Michael Greenbaum, Collin Meeker, Spencer Lee, Guimu Guo, "Accelerating Maximal Quasi-Clique Mining using the GPU", CSM Student Research Day, (2023).
Academic Reviews
- - External Reviewer under Guimu Guo, The 26th Pacific-Asian Conference on Knowledge Discovery and Data Mining (PAKDD), (2023).
Projects
Accelerating Maximal Quasi-Cliques using GPUs | cuQC
The first GPU-accelerated maximal quasi-clique mining algorithm. This program can accelerate the enumeration of all maximal quasi-cliques by up to 4000% compared to the CPU algorithm. Developed by the High-Performance Data Mining Lab at Rowan University and external researchers.
Project Manager: Michael Greenbaum Members: Ke Fan, Sidhartha Kumar, Guimu GuoGitHub: Mike12041204 - cuQC