RethinkFL
by WenkeHuang
CVPR2023 - Rethinking Federated Learning with Domain Shift: A Prototype View
AI summary
Domain adaptation
Improves federated learning performance by incorporating domain knowledge and regularization to adapt models across diverse domains
- stars
- 93
- forks
- 13
- watching
- 1
Similar projects
Found by comparing what the projects do, not just their names.
Federated Learning Framework
A framework for tackling heterogeneity and catastrophic forgetting in federated learning by leveraging cross-correlation and similarity learning
Domain adaptation library
An implementation of a federated learning method to reduce domain bias in representation space, enabling improved knowledge transfer between clients and servers.
Deep learning adaptation
An implementation of adaptive test-time personalization for federated learning in deep neural networks.
Federated learner
Federated learning algorithm that adapts to non-IID data by decoupling and correcting for local drift
Federated Learning Framework
Develops an alignment framework for federated learning with non-identical client class sets
Domain adaptation software
Develops a method to improve performance of computer vision tasks by adapting models to new domains and data sources through meta-learning and self-learning techniques.
Federated Learning Engine
An implementation of cross-silo federated learning with adaptability to statistical heterogeneity
Domain adaptation model
This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another.
Domain generalization method
This project presents a method for federated domain generalization with adjustment, allowing multiple models to learn from each other across different domains.
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 Framework
Evaluates various methods for federated learning on different models and tasks.
Federated Learning Framework
An implementation of a personalized federated learning framework with decentralized sparse training and peer-to-peer communication protocol.
Domain adaptation library
A collection of implementations of algorithms to adapt deep learning models from one domain to another
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data
Personalization software
Improves machine learning models for personalized performance under evolving test distributions in distributed environments
