FedStar
by yuetan031
[AAAI'23] Federated Learning on Non-IID Graphs via Structural Knowledge Sharing
AI summary
Graph classifier
This project implements a federated learning algorithm for non-IID graph classification tasks by leveraging structural knowledge sharing.
- stars
- 60
- forks
- 13
- watching
- 1
Similar projects
Found by comparing what the projects do, not just their names.
Federated Learning
This project enables personalized federated learning with inferred collaboration graphs to improve the performance of machine learning models on non-IID (non-independent and identically distributed) datasets.
Federated Learning Framework
Develops an alignment framework for federated learning with non-identical client class sets
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data
Federated learner
Federated learning algorithm that adapts to non-IID data by decoupling and correcting for local drift
Federated learning model
A Python implementation of Personalized Federated Learning with Graph using PyTorch.
Federated Learning Study
The purpose of this project is to investigate the convergence of a federated learning algorithm on non-IID (non-identically and independently distributed) data.
Federated learning library
An implementation of federated learning with prototype-based methods across heterogeneous clients
Graph classifier
A PyTorch implementation of a semi-supervised graph classification model that learns hierarchical representations from labeled and unlabeled graph data.
Federated Learning Framework
A framework for non-IID federated learning via neural propagation
Federated Learning Algorithm
An unsupervised federated learning algorithm that uses cross knowledge distillation to learn meaningful data representations from local and global levels.
Graph classifier
An implementation of a graph classification model using structural attention and PyTorch
Federated Learner
An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships
Federated Learning Experiment
An experiment comparing different federated learning approaches for image classification tasks with non-iid datasets.
Federated Learning Framework
Evaluates various methods for federated learning on different models and tasks.
Federated Learning Approach
This project presents an approach to federated learning that leverages unsupervised techniques to adapt models to unlabeled data without requiring labels.