Hyperbolic embeddings compress graphs 42% better than state-of-the-art
New lossless algorithm uses curved geometry to shrink real-world networks by nearly half.
Deep Dive
Researchers Celinska-Kopczynska and Kopczynski introduce a fast lossless graph compression algorithm that leverages modern hyperbolic embedders. Tested on real-world and generated networks, their method beats state-of-the-art compressors by up to 42% on real-world graphs.
Key Points
- Lossless compression using hyperbolic geometry beats existing methods by up to 42% on real-world graphs.
- Method exploits the natural hyperbolic structure of scale-free networks (social, web, biological).
- Fast algorithm suitable for large graphs, with perfect reconstruction guaranteed.
Why It Matters
Near-halving storage needs for massive graphs cuts costs and speeds up network analysis at scale.