FedOV
Towards Addressing Label Skews in One-Shot Federated Learning (ICLR 2023)
AI summary
Federated Learning Framework
Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models.
- stars
- 17
- forks
- 3
- watching
- 2
Similar projects
Found by comparing what the projects do, not just their names.
Federated Learning Framework
A framework that enables federated learning across multiple datasets while optimizing model performance with record similarities.
Federated learning algorithm
A C++ implementation of a federated learning algorithm for decision trees, enabling multiple parties to jointly learn from their private data without sharing it.
Federated Learning System
A system for distributed machine learning using tree-based models with secure aggregation and differential privacy features.
Data Fusion Tool
This project enables federated learning across partially class-disjoint data with curated bilateral curation.
Federated Learning Framework
A framework for collaborative distributed machine learning in enterprise environments.
Federated Learning framework
An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources.
Federated learning framework
An open-source repository implementing various federated learning algorithms with source code for multiple deep learning applications.
Federated Learning Framework
Develops a framework to balance competing goals in federated learning by decoupling generic and personalized prediction tasks.
Federated learner
This project presents a federated semi-supervised learning approach to improve model performance on multiple datasets by leveraging random sampling consensus.
Federated Learning Framework
Evaluates various methods for federated learning on different models and tasks.
Federated learning model
A Python implementation of Personalized Federated Learning with Graph using PyTorch.
Federated learning framework
Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions.
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
An open source federated learning framework designed to be secure, scalable and easy-to-use for enterprise environments
Federated Learning Framework
A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems.