Hyperdimensional Computing Classifier

Hyperdimensional computing (HDC) classifiers leverage high-dimensional vector representations and operations for efficient machine learning, particularly on resource-constrained devices. Current research focuses on improving HDC classifier accuracy and efficiency through techniques like active learning to optimize data annotation, ensemble methods to combine multiple classifiers, and learning-based approaches to refine the training process. These advancements offer significant potential for improving the performance and applicability of HDC in various domains, including embedded systems and Internet of Things applications, by reducing computational complexity and memory requirements compared to traditional deep learning methods.