New paper explores federated learning and explainable AI integration for privacy-preserving transparent machine learning
Read the original at arxiv.org→arXiv:2607.13045v1 Announce Type: new Abstract: Federated Learning (FL) has emerged as a key paradigm for privacy-preserving collaborative model training across distributed and heterogeneous data sources. By keeping...
Original headline: "Federated Explainable Artificial Intelligence: Roles, Architectures, Evaluation, and Open Challenges"