Byzantine-Robust Decentralized Federated Learning
Minghong Fang, Zifan Zhang, et al.
CCS 2024
We present a technique for approximating sequences of linear programs with varying right-hand sides and study the geometric properties of this approximation. Our approximation has an efficiency advantage over optimal solutions. When applied to deterministic control problems, the suggested technique outperforms the linear feedback model and provides accurate results (error of 5.8% in our numerical example). Numerical experience with stochastic models indicates that this approach may outperform the limited lookahead policies while maintaining low computational requirements.
Minghong Fang, Zifan Zhang, et al.
CCS 2024
Mario Blaum, John L. Fan, et al.
IEEE International Symposium on Information Theory - Proceedings
Andrew Skumanich
SPIE Optics Quebec 1993
Nimrod Megiddo
Journal of Symbolic Computation