CECILIA: Comprehensive Secure Machine Learning Framework. (arXiv:2202.03023v2 [cs.LG] UPDATED)

Since ML algorithms have proven their success in many different applications,
there is also a big interest in privacy preserving (PP) ML methods for building
models on sensitive data. Moreover, the increase in the number of data sources
and the high computational power required by those algorithms force individuals
to outsource the training and/or the inference of a ML model to the clouds
providing such services. To address this, we propose a secure 3-party
computation framework, CECILIA, offering PP building …

framework lg machine machine learning