Spanners in Hypergraphs
In this work, we explore parallel construction of spanners in hypergraphs. Spanners include all vertices and a subset of edges while ensuring shortest distances within an allowable stretch, making them crucial for efficiently approximating graph structures. We build on the state-of-the-art algorithm for parallel graphs spanners and extend it for hypergraphs focusing on optimizing the size without compromising stretch. We propose techniques to address memory and performance challenges when dealing with hypergraphs.
Authors
- Yogish Sabharwal (ORCID: https://orcid.org/0009-0002-5053-2059)
- Maulein Pathak (ORCID: https://orcid.org/0009-0007-7722-524X)
- Neelima Gupta (ORCID: https://orcid.org/0000-0002-0870-0824)
Institutions
- University of Delhi (IN)
- IBM Research - India (IN)
Publication Details
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1109/hipcw63042.2024.00085
- Primary Topic
- Advanced Graph Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00