• Communication-Efficient Online Federated Learning Framework for Nonlinear Regression 

      Gogineni, Vinay Chakravarthi; Werner, Stefan; Huang, Yih-Fang; Kuh, Anthony (Peer reviewed; Journal article, 2022)
      Federated learning (FL) literature typically assumes that each client has a fixed amount of data, which is unrealistic in many practical applications. Some recent works introduced a framework for online FL (Online-Fed) ...
    • Decentralized PMU-Assisted Power System State Estimation With Reduced Interarea Communication 

      Kashyap, Neelabh; Werner, Stefan; Huang, Yih-Fang (Journal article; Peer reviewed, 2018)
      This paper presents a decentralized approach to multiarea power system state estimation using a combination of conventional measurement devices and newer phasor measurement units (PMU). We employ a reduced-order approach ...
    • Nonlinear adaptive filtering with kernel set-membership approach 

      Chen, Kewei; Werner, Stefan; Huang, Yih-Fang; Kuh, Anthony (Peer reviewed; Journal article, 2020)
      This paper develops nonlinear kernel adaptive filtering algorithms based on the set-membership filtering (SMF) framework. The set-membership-based filtering approach is distinct from the conventional adaptive filtering ...
    • On Stability and Convergence of Distributed Filters 

      Talebi, Sayedpouria; Werner, Stefan; Gupta, Vijay; Huang, Yih-Fang (Peer reviewed; Journal article, 2021)
      Recent years have bore witness to the proliferation of distributed filtering techniques, where a collection of agents communicating over an ad-hoc network aim to collaboratively estimate and track the state of a system. ...