Google WMVI
Project Opportunity – Equilibrium-based Federated Learning via Online Optimization in Games: Better, Stronger, Faster
Research Description –Federated learning (FL) poses a fundamental challenge to learning algorithms, which is captured by the
prevalent networking, communication, and privacy bottlenecks. In fact, research in FL has largely been driven by these constraints bottom up. In stark contrast, our project takes a top-down rethinking of FL, starting from
primal-dual reformulations towards the flexible and powerful online learning in games perspective. The two research fields have been evolving largely in isolation despite the strong connections, which this project will
bridge through the research questions towards better, stronger, and faster FL.