Výsledky vyhľadávania - "mean Hessian theorem"

Unified Analysis of Decentralized Gradient Descent: A Contraction Mapping Framework

Autori: Larsson, Erik G Michelusi, Nicolo

Zdroj: IEEE Open Journal of Signal Processing. 6:507-529

Predmety: Topology, Noise measurement, Convergence, Noise, Vectors, Symmetric matrices, Signal processing algorithms, Network topology, Optimization, Heuristic algorithms, Decentralized machine learning, decentralized optimization, decentralized gradient descent (DGD), diffusion, stochastic DGD and diffusion, federated learning, communication noise, random topology, link failures, convergence, contractions, fixed points, mean Hessian theorem

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-214240
https://doi.org/10.1109/OJSP.2025.3557332