Sparse Federated Representation Learning for deep-sea exploration habitat design for low-power autonomous deployments

The author explores federated learning to overcome latency challenges in voluminous sensor data from multi-robotic autonomous vehicles, optimizing processing in low-bandwidth environments. This approach seeks a distributed alternative to centralized data synchronization through distributed model updates.