Taming backdoors in federated learning with FLAME
Some machine learning training pipelines require data from confidential sources (such as audio clips from private conversations, written content from private messages, or pictures stored on mobile devices). To enable the use of confidential (e.g., privacy-sensitive) data for machine learning purposes, federated learning has emerged as new training paradigm.