Hyperdimensional Computing

Hyperdimensional computing (HDC) is a brain-inspired computing paradigm that uses high-dimensional random vectors to represent and process information, aiming for efficient and robust machine learning. Current research focuses on developing novel HDC algorithms and architectures for various applications, including graph classification, time series forecasting, and image recognition, often incorporating techniques like federated learning and active learning to improve efficiency and data usage. HDC's lightweight nature and potential for improved energy efficiency and explainability make it a significant area of research with implications for resource-constrained devices and applications requiring real-time processing.