centralized-learning

This repository provides a comprehensive solution and codebase for the migration from centralized to federated learning. It demonstrates centralized training, its drawbacks, and how federated learning addresses these issues. It also serves as a tutorial to guide users through the transition process.

Multi agent reinforcement learning: PyTorch implementations of several algorithms for Multi Agent domains

Framework of Distributed Learning in Vehicular Networks

FedSentry is a research-driven prototype designed to secure heterogeneous and distributed IoT networks using federated learning (FL). Built on the CICIoT2023 dataset, the project explores centralized and federated training paradigms (FedAvg, FedProx) to detect diverse cyberattacks while preserving data privacy across distributed nodes.

Legacy code from PettingZoo environment. Centralized learning, de-centralized execution.

Experiments involving client participation and data distributions on FedAvg algorithm