The Large-scale dAta manaGement, Analytics, and Science (LAGAS) Group is a team of researchers dedicated to exploring the expansive and multifaceted domain of data science. With an increasing focus on data management and analytics, the group is committed to developing scalable and efficient algorithms and techniques designed to handle diverse data types and complexities. Their research spans a wide array of applications, including social network analysis, recommendation systems, information retrieval, and beyond. By embracing broader research methodologies and directions, the group aims to drive innovation in data science and tackle real-world challenges using cutting-edge technology. Through their efforts, the LAGAS Group seeks to push the boundaries of data science and contribute valuable insights to the field.
LAGAS Group, HKBU
Large-scale dAta manaGement, Analytics and Science
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HKBU-LAGAS/.github’s past year of commit activity - ClustGDD Public
the official implementation of KDD2025 paper "Simple yet Effective Graph Distillation via Clustering"
HKBU-LAGAS/ClustGDD’s past year of commit activity - Locle Public
HKBU-LAGAS/Locle’s past year of commit activity - S2CAG Public
The official implementation of the KDD2025 paper "Spectral Subspace Clustering for Attributed Graphs"
HKBU-LAGAS/S2CAG’s past year of commit activity - TADA Public
the official implementation of KDD2024 paper "Efficient Topology-aware Data Augmentation for High-Degree Graph Neural Networks"
HKBU-LAGAS/TADA’s past year of commit activity - SAFT Public
HKBU-LAGAS/SAFT’s past year of commit activity - awesome-cpp Public archive Forked from fffaraz/awesome-cpp
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
HKBU-LAGAS/awesome-cpp’s past year of commit activity - TPC Public
The official implementation of the KDD 2024 paper "Effective Clustering on Large Attributed Bipartite Graphs"
HKBU-LAGAS/TPC’s past year of commit activity
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