Can Short Hypervectors Drive Feature-Rich GNNs? Strengthening the Graph Representation of Hyperdimensional Computing for Memory-efficient GNNs

Hyperdimensional computing (HDC) based GNNs are significantly advancing the brain-like cognition in terms of mathematical rigorousness and computational tractability. However, the researches in this field seem to have a "long vector consensus" that the length of HDC-hypervectors must be de...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	2025 62nd ACM/IEEE Design Automation Conference (DAC) S. 1 - 7
Hauptverfasser:	Wang, Jihe, Han, Yuxi, Wang, Danghui
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 22.06.2025
Schlagworte:	Accuracy Cognition Design automation Distortion Feature extraction GNN graph representation hyperdimensional computing memory Memory management Training Vectors
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!