论文标题
可信赖的生物医学高维计算的使用证明的工作区块链
Proof-of-Useful-Work Blockchain for Trustworthy Biomedical Hyperdimensional Computing
论文作者
论文摘要
高维计算（HDC）是一种有前途的生物启发的学习范式，它的优势在平衡性能和效率方面，并且已越来越多地应用于生物密码领域。在生物医学应用中，训练有素的学习模型的可复制性和验证性等可信度至关重要。在这项工作中，我们介绍了HDCoin，这是HDC的第一个使用证明的区块链框架。使用HDCOIN，我们将常规浪费的采矿过程转变为一个竞争过程，以开发高准确性，值得信赖和可验证的高维模型。我们探索了四个不同的生物医学数据集，并对区块链矿工的关键HDC超级参数进行了广泛的设计空间探索，例如维度，学习率和重新迭代，以实现模型性能，适应性挖掘的难度和公平性，以实现使用证明。
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.
