This folder contains advanced examples for NVFlare.

Please make sure you set up a virtual environment and install JupyterLab following the example root readme.

Please also install "./requirements.txt" in each example folder.

• Federated Learning with CIFAR-10
  • Simulated Federated Learning with CIFAR-10
    • This example includes instructions on running FedAvg, FedProx, FedOpt, and SCAFFOLD algorithms using NVFlare's FL simulator.
  • Real-world Federated Learning with CIFAR-10
    • Includes instructions on running FedAvg with streaming of TensorBoard metrics to the server during training and homomorphic encryption.
• Federated XGBoost
  • Includes examples of histogram-based algorithm, tree-based. Tree-based algorithms also includes bagging and cyclic approaches.

• Federated Linear Model with Scikit-learn
  • Shows how to use the NVIDIA FLARE with scikit-learn, a widely used open-source machine learning library.
• Federated K-Means Clustering with Scikit-learn
  • NVIDIA FLARE with scikit-learn and k-Means.
• Federated SVM with Scikit-learn
  • NVIDIA FLARE with scikit-learn and SVM.
• Federated Learning for Random Forest based on XGBoost
  • Example of using NVIDIA FLARE with scikit-learn and Random Forest.

• Federated Learning with Differential Privacy for BraTS18 segmentation
  • Illustrates the use of differential privacy for training brain tumor segmentation models using federated learning.
• Federated Learning for Prostate Segmentation from Multi-source Data
  • Example of training a multi-institutional prostate segmentation model using FedAvg, FedProx, and Ditto.

• Financial Application with Federated XGBoost Methods
  • Illustrates the use of NVFlare on a financial application using XGBoost to train a model in a federated manner.

• Swarm Learning
  • Example of swarm learning with NVIDIA FLARE using PyTorch with the CIFAR-10 dataset.

• Vertical Federated Learning
  • Example of running split learning using the CIFAR-10 dataset.
• Vertical Federated XGBoost
  • Example of vertical federated learning with NVIDIA FLARE on tabular data.

• Federated Statistic Overview
  • Discuss the overall federated statistics features
• Federated Statistics for Medical Imaging
  • Example of gathering local image histogram to compute the global dataset histograms.
• Federated Statistics for DataFrame
  • Example of gathering local statistics summary from Pandas DataFrame to compute the global dataset statistics.
• Federated Hierarchical Statistics
  • Example of generating federated hierarchical statistics for data that can be represented as Pandas DataFrame.

• Federated Policies
  • Discuss the federated site policies for authorization, resource and data privacy management

• Custom Authentication
  • Example demonstrating custom authentication policy

• Job-level Authorization
  • Example demonstrating job-level authorization policy

• Hello PyTorch with TensorBoard Streaming
  • Example building upon Hello PyTorch showcasing the TensorBoard streaming capability from the clients to the server.
• Experiment Tracking with MLflow and Weights and Biases
  • Example showing the use of the Writers and Receivers in NVFlare to write to different experiment tracking systems.

• FL Hub
  • Allow hierarchical interaction between several levels of nvflare FL systems, e.g. Tier-1 (hub) and Tier-2 (sub-systems).