1st Workshop on Federated Learning Technologies

Mirko Polato, Roberto Esposito, Walter Riviera, Zenglin Xu, Irwin King

Abstract: AI-based systems, especially those based on machine learning technologies, have become central in modern societies. In the meanwhile, users and legislators are becoming aware of privacy issues. Users are increasingly reluctant in sharing their sensitive information, and new laws have been enacted to regulate how private data is handled (e.g., the GDPR). Federated Learning (FL) has been proposed to develop better AI systems without compromising users’ privacy and the legitimate interests of private companies. Although still in its infancy, FL has already shown significant theoretical and practical results making FL one of the hottest topics in the machine learning community. Given the considerable potential in overcoming the challenges of protecting users’ privacy while making the most of available data, we propose a workshop on Federated Learning Technologies (FLT) at TheWebConf 2023. The goal of this workshop is to focus the attention of the TheWebConf research community on addressing the open questions and challenges in this thriving research area. Given the broad range of competencies in the TheWebConf community, the workshop will welcome foundational contributions as well as contributions expanding the scope of these techniques, such as improvements in the interpretability and fairness of the learned models.