NAACL '24 (Demo) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference
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Updated
May 30, 2024 - Python
NAACL '24 (Demo) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference
An open framework for Federated Learning.
Federated Learning with Candle
Comparing centralised machine learning and federated learning using flower framework. Building a custom strategy over the base FedAvg called FedCustom which has a higher learning rate and several other hyper parameters to increase the accuracy.
Blades: A Unified Benchmark Suite for Byzantine Attacks and Defenses in Federated Learning
The implementation of FedAvg based on pytorch .
PyTorch implementation of federated learning on MNIST
Using FedAvg method to predict future temperature.
Handy PyTorch implementation of Federated Learning (for your painless research)
A classic implementation of Federated Learning for identifying FALL and ADL from images with Transfer Learning.
An FL algorithm inspired by FedGMA
Simple implementation of FedAvg, a Federated Learning algorithm.
Implementation of FedNCF with SecAvg
Experiments of the FL in Healthcare project - MRI images use case - using Flower
We utilize the Adversarial Model Perturbations (AMP) regularizer to regularize clients’ models. The AMP regulzaizer is based on perturbing the model parameters so as to get a more generalized model. The claim of AMP regularizer is to reach flat minima and therefore is expected to reach flat minima in FL settings as well.
A Open Source Federated Learning Simulation Framework for Everyone
Federated Learning for Swarm Robotics
(NeurIPS 2022) Official Implementation of "Preservation of the Global Knowledge by Not-True Distillation in Federated Learning"
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