Proof-of-Useful-Work Blockchain for Trustworthy Biomedical Hyperdimensional Computing

TL;DR

This paper introduces HDCoin, a blockchain framework that uses proof-of-useful-work to develop trustworthy biomedical hyperdimensional models, enhancing model verifiability and fairness.

Contribution

It presents the first blockchain system for hyperdimensional computing that transforms mining into a process for creating accurate, trustworthy biomedical models.

Findings

HDCoin achieves high accuracy on biomedical datasets.

Adaptive mining difficulty improves fairness.

Hyperparameter tuning enhances model performance.

Abstract

Hyperdimensional Computing (HDC) is a promising bio-inspired learning paradigm for its advantage of balancing performance and efficiency and has been increasingly applied to the bio-medical domain. In bio-medical applications, trustworthiness such as replicability and verifiability of the trained learning models is crucial. In this work, we introduce HDCoin, the first proof-of-useful-work blockchain framework for HDC. With HDCoin, we transform the conventional energy-wasteful mining process into a competitive process for developing high accuracy, trustworthy and verifiable hyperdimensional models. We explore four diverse biomedical datasets, and conduct an extensive design-space exploration of key HDC hyperparameters of blockchain miners such as dimensionality, learning rate, and retraining iterations for model performance, adaptive mining difficulty and fairness on proof-of-useful-work.