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asynchronous-federated-learning-based-mobility-aware-caching-in-vehicular-edge-computing

awesome-federated-machine-learning

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

cluster

The codes的K-means，FCM，谱聚类，DBSCAN，AP（AffinityPropagation），DPC聚类算法比较

dolphins

Main code of Dolphins dataset

learn-compresscsi-ra-v2x-code

Code for Learn to Compress CSI and Allocate Resources in Vehicular Networks

marlspectrumsharingv2x

Spectrum sharing in vehicular networks based on multi-agent reinforcement learning, IEEE Journal on Selected Areas in Communications

pfl-non-iid

The origin of the Non-IID phenomenon is the personalization of users, who generate the Non-IID data. With Non-IID (Not Independent and Identically Distributed) issues existing in the federated learning setting, a myriad of approaches has been proposed to crack this hard nut. In contrast, the personalized federated learning may take the advantage of the Non-IID data to learn the personalized model for each user. Thanks to @Stonesjtu, this platform can also record the GPU memory usage for the model.

rav2x

Resource allocation in V2X

v2x-sim

[RA-L2022] V2X-Sim Dataset and Benchmark