DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification

• URL: http://arxiv.org/abs/2304.05503v1
• Date: Tue, 11 Apr 2023 21:18:52 GMT
• Title: DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification
• Authors: Junyao Wang, Sitao Huang, Mohsen Imani
• Abstract summary: We propose DistHD, a novel dynamic encoding technique for HDC adaptive learning. Our proposed algorithm DistHD successfully achieves the desired accuracy with considerably lower dimensionality.
• Score: 10.535034643999344
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Brain-inspired hyperdimensional computing (HDC) has been recently considered a promising learning approach for resource-constrained devices. However, existing approaches use static encoders that are never updated during the learning process. Consequently, it requires a very high dimensionality to achieve adequate accuracy, severely lowering the encoding and training efficiency. In this paper, we propose DistHD, a novel dynamic encoding technique for HDC adaptive learning that effectively identifies and regenerates dimensions that mislead the classification and compromise the learning quality. Our proposed algorithm DistHD successfully accelerates the learning process and achieves the desired accuracy with considerably lower dimensionality.

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