A self-evaluation by the scheme's co-designer of a black-box 'homomorphic AI' hash reports perfect clustering on one dataset but degraded off-the-shelf accuracy on Fashion-MNIST, improved only after custom post-hoc tuning.
Leveraging TenSEAL: A Comparative Study of BFV and CKKS Schemes for Training ML Models on Encrypted IoT Data
1 Pith paper cite this work, alongside 5 external citations. Polarity classification is still indexing.
1
Pith paper citing it
5
external citations · OpenAlex
fields
cs.CR 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Technical Evaluation of a Disruptive Approach in Homomorphic AI
A self-evaluation by the scheme's co-designer of a black-box 'homomorphic AI' hash reports perfect clustering on one dataset but degraded off-the-shelf accuracy on Fashion-MNIST, improved only after custom post-hoc tuning.