See through Gradients: Image Batch Recovery via GradInversion
See through Gradients: Image Batch Recovery via GradInversion
Training deep neural networks requires gradient estimation from data batches to update parameters. Gradients per parameter are averaged over a set of data and this has been presumed to be safe for privacy-preserving training in joint, collaborative, and federated learning applications. Prior work only showed the possibility of recovering input …