Keynote Speaker
Prof. Jian PEI
Professor and Chair, Duke University Department of Computer Science, Trinity College of Arts & Sciences; Professor, Duke University Department of Biostatistics and Bioinformatics, School of Medicine; Professor of Electrical and Computer Engineering, Pratt School of Engineering
Title: Data valuation in federated learning
Abstract
To enable practical federated learning, we have to not only improve the efficiency but also address the incentive and fairness concerns. In this talk, I will delve into the challenges in valuation and personalization in federated learning and share our recent endeavors. Particularly, valuation in federated learning seeks to allocate credits to participants in a just and equitable manner. Personalization in federated learning addresses the individual needs of participants. In the context of federated learning, those problems have some unique challenges. For example, the federated learning process is often run only once and many participants may not be consulted in every round. I will discuss the intuitions and ideas of our latest methods and also discuss some challenges and opportunities for future work.
