• Personalized Online Federated Learning for IoT/CPS: Challenges and Future Directions 

      Gogineni, Vinay Chakravarthi; Werner, Stefan; Gauthier, Francois; Huang, Yih-Fang; Kuh, Anthony (Journal article, 2022)
      In recent years, federated learning (FL) has emerged as a powerful paradigm for distributed learning thanks to its privacy-preserving capabilities. With the use of FL, a network of edge devices can make intelligent decisions ...
    • Privacy-Preserving Distributed Learning with Nonsmooth Objective Functions 

      Gauthier, Francois; Gratton, Cristiano; Dasanadoddi Venkategowda, Naveen Kumar; Werner, Stefan (Chapter, 2021)
      This paper develops a fully distributed differentially-private learning algorithm based on the alternating direction method of multipliers (ADMM) to solve nonsmooth optimization problems. We employ an approximation of the ...
    • Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression 

      Gauthier, Francois; Gogineni, Vinay Chakravarthi; Werner, Stefan; Huang, Yih-Fang; Kuh, Anthony (Chapter, 2022)
      Many assumptions in the federated learning literature present a best-case scenario that can not be satisfied in most real-world applications. An asynchronous setting reflects the realistic environment in which federated ...