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communication-efficiency 开源项目推荐(16 个)
communication-efficiency 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 全部 16
GitHub 共 16 个仓库,已全部展示All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
🏆 Official implementation of LangCoop: Collaborative Driving with Natural Language
Paper list of federated learning: About system design
FedAnil+ is a novel lightweight, and secure Federated Deep Learning Model to address non-IID data, privacy concerns, and communication overhead. This repo hosts a simulation for FedAnil+ written in Python.
The communication efficiency of federated learning is improved by sparsifying the parameters uploaded by the clients.
This project implements communication-efficient online federated learning strategies for resource-constrained devices using random Fourier features (RFFs) for kernel regression. It reduces communication overhead through partial-sharing and event-triggered updates, ensuring efficient local model updates.
Federated Dropout with transfer learning. Clients train reduced submodels to cut communication cost, trading a little accuracy for much smaller updates.
Communication-Efficient Federated Learning via Transferring Codebooks
Communication-efficient federated learning through adaptive weight clustering and server-side distillation.
Hybrid Federated Learning with Structured Model Pruning and Gradient Sparsification on MNIST
This work is a journal paper published at The Journal of Supercomputing in 2023, focusing on improving communication efficiency of a distributed learning system using age-based worker selection techniques.
FedCVAE-based federated knowledge distillation with drift-triggered sparse communication.
图增强联邦推荐:Top-k 稀疏上传 + 误差反馈 + 自适应聚类 + 簇内图聚合;单轮上传开销较最优基线降低约 88.6%。已被《小型微型计算机系统》录用。
This repository implements a communication-efficient online federated learning framework for nonlinear regression using partial sharing. Clients update local models with streaming data and share only portions of those updates with the server, reducing communication overhead while maintaining performance.
Codebase for my thesis: 'Investigating the Αpplicability of Federated Dynamic Averaging in Federated Low-Rank Adaptation Architectures'
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 16 个项目;原始页面见 https://github.com/topics/communication-efficiency。
- 该话题在 GitHub 上共有 16 个仓库, 本站收录的是其中最热门的 16 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 16 个项目累计 2870 Star,覆盖 3 种主要语言,数据更新于 2026-11-08。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。