Apple Privacy-Preserving Machine Learning Workshop 2022

Earlier this year, Apple hosted the Workshop on Privacy-Preserving Machine Learning (PPML). This virtual event brought Apple and members of the academic research communities together to discuss the state of the art in the field of privacy-preserving machine learning through a series of talks and discussions over two days. In this post we will introduce a new dataset for community benchmarking in PPML, and share highlights from workshop discussions and recordings of select workshop talks. Significant advances in machine learning (ML) over the last decade have been driven in part by the increased accessibility of both large-scale computing and training data. By competing to improve standard benchmarks on datasets like ImageNet, the community has discovered an array of improved techniques, optimizations, and model architectures that are broadly applicable and of proven value.