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Found 4 papers, 0 papers with code
Federated Learning with Data-Agnostic Distribution Fusion
In this paper, we propose a novel data-agnostic distribution fusion based model aggregation method called \texttt{FedDAF} to optimize federated learning with non-IID local datasets, based on which the heterogeneous clients' data distributions can be represented by the fusion of several virtual components with different parameters and weights.
Federated Learning with Decoupled Probabilistic-Weighted Gradient Aggregation
In this paper, we proposed a novel decoupled probabilistic-weighted gradient aggregation approach called FeDEC for federated learning.
PingAn: An Insurance Scheme for Job Acceleration in Geo-distributed Big Data Analytics System
Geo-distributed data analysis in a cloud-edge system is emerging as a daily demand.
Distributed, Parallel, and Cluster Computing
Designing a Disaster-resilient Network with Software Defined Networking
Our design consists of a sub-graph based proactive protection approach on the data plane and a splicing approach at the controller for effective restoration on the control plane.
Networking and Internet Architecture Distributed, Parallel, and Cluster Computing
