TsingZ0/FL-IoT

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44
Rank 634,578 (Top 13 %)
Language
Python
License
MIT License
Created over 2 years ago
Updated over 2 years ago

TsingZ0/FL-IoT

TsingZ0

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This is a platform containing the datasets and federated learning algorithms in IoT environments.

PFLlib

We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study

FedALA

AAAI 2023 accepted paper, FedALA: Adaptive Local Aggregation for Personalized Federated Learning

HtFLlib

Configure one file for model heterogeneity. Consistent GPU memory usage for single or multiple clients.

TLSAN

This is our implementation for our paper: TLSAN: Time-aware Long- and Short-term Attention Network for Next-item Recommendation

FedTGP

AAAI 2024 accepted paper, FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning

FedCP

KDD 2023 accepted paper, FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy

FedKTL

CVPR 2024 accepted paper, An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning

GPFL

ICCV 2023 accepted paper, GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning

DBE

NeurIPS 2023 accepted paper, Eliminating Domain Bias for Federated Learning in Representation Space

SHAN

This is the implementation for the paper: Sequential Recommender System based on Hierarchical Attention Network

ICE6405P-260-M01

Course materials

LSPM

This is the implementation for the paper: Online Personalized Next-Item Recommendation via Long Short Term Preference Learning

TsingZ0