Statistics for topic federated-learning
RepositoryStats tracks 569,482 Github repositories, of these 197 are tagged with the federated-learning topic. The most common primary language for repositories using this topic is Python (130). Other languages include: Jupyter Notebook (19)
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Perform data science on data that remains in someone else's server
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
✨✨A curated list of latest advances on Foundation Models with Federated Learning
This is a platform containing the datasets and federated learning algorithms in IoT environments.
联邦学习模块化框架，支持各类FL。A universal federated learning framework, free to switch thread and process modes
Perform data science on data that remains in someone else's server
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
✨✨A curated list of latest advances on Foundation Models with Federated Learning
This is a platform containing the datasets and federated learning algorithms in IoT environments.
P2PFL is a decentralized federated learning library that enables federated learning on peer-to-peer networks using gossip protocols, making collaborative AI model training possible without reliance on...
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
Perform data science on data that remains in someone else's server
Federated learning framework made by researchers for researchers :)
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
✨✨A curated list of latest advances on Foundation Models with Federated Learning
🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)
P2PFL is a decentralized federated learning library that enables federated learning on peer-to-peer networks using gossip protocols, making collaborative AI model training possible without reliance on...
Simulation framework for accelerating research in Private Federated Learning
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.
Fast integration of backdoor attacks in machine learning and federated learning.
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on a...
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
A unified framework for privacy-preserving data analysis and machine learning
Configure one file for model heterogeneity. Consistent GPU memory usage for single or multiple clients.
Federated learning framework made by researchers for researchers :)
NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference
[IoTDI 2023/ML4IoT 2023] Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. arXiv:2307.09218.