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14 篇16 篇
30 篇深度技术笔记
机器学习与联邦学习
纵向联邦学习 (VFL)、个性化联邦学习、模型蒸馏 (FedMD/FedFD)、强化学习算法与分布式协同训练。
传统机器学习
联邦学习
联邦学习中的基础算法介绍 2024-10-28
Advances and Open Problems in Federated Learning 2023-09-06
Vertical Federated Learning Concepts,Advances, and Challenges 2024-05-11
机器学习中的并行计算 2024-05-12
Boosted Trees 简介 2024-05-14
SecureBoost：一种无损的联邦学习框架 2024-05-14
FedGen & Data-Free Knowledge Distillation for Heterogeneous Federated Learning 2024-07-10
Towards Personalized Federated Learning 2024-09-21
Distilling the Knowledge in a Neural Network 2024-10-09
FedMD & Heterogenous Federated Learning via Model Distillation 2024-10-14
FedFTG & Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning 2024-10-24
MOON & Model-Contrastive Federated Learning 2024-10-30
Knowledge Distillation in Federated Learning:A Practical Guide 2024-11-26
DKD-pFed & A novel framework for personalized federated learning via decoupling knowledge distillation and feature decorrelation 2024-12-24
pFedSD & Personalized Edge Intelligence via Federated Self-Knowledge Distillation 2024-12-26
FedFD&FAug:Communication-Efficient On-Device Machine Learning:Federated Distillation and Augmentation under Non-IID Private Data 2025-01-09