Found by comparing what the projects do, not just their names.
Federated Learning System
An implementation of semi-supervised federated learning for improving the performance of a server using distributed clients with unlabeled data
Federated Learning framework
An implementation of heterogeneous federated learning with parallel edge and server computation
Federated learning library
An implementation of federated learning with prototype-based methods across heterogeneous clients
Federated learning framework
Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions.
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data
Federated Learning Algorithm
An algorithm for balancing utility and privacy in federated learning on heterogeneous data
Federated Learning framework
An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources.
Federated learning method
A method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness
Federated Learning Framework
A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems.
Federated Learning Framework
An implementation of a federated learning framework for handling data heterogeneity in decentralized settings
Federated Learning Experiments
Numerical experiments for private federated learning with communication compression algorithms
Federated Learning Framework
A framework for collaborative distributed machine learning in enterprise environments.
Federated Learning Algorithms
Implementation of various federated learning algorithms to mitigate dimensional collapse in heterogeneous federated learning environments
Federated Learning Algorithm
This project presents an approach to federated learning with partial client participation by optimizing anchor selection for improving model accuracy and convergence.
Federated Learning Algorithm
An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data