Hierarchical fuzzy neural networks with privacy preservation for heterogeneous big data. (arXiv:2209.08467v1 [cs.LG])

Heterogeneous big data poses many challenges in machine learning. Its
enormous scale, high dimensionality, and inherent uncertainty make almost every
aspect of machine learning difficult, from providing enough processing power to
maintaining model accuracy to protecting privacy. However, perhaps the most
imposing problem is that big data is often interspersed with sensitive personal
data. Hence, we propose a privacy-preserving hierarchical fuzzy neural network
(PP-HFNN) to address these technical challenges while also alleviating privacy
concerns. The network is trained with a …

big big data data networks neural networks preservation privacy