UAM

Sparse Federated Representation Learning for autonomous urban air mobility routing during mission-critical recovery windows

The author describes their journey to sparse federated representation learning, prompted by communication overhead challenges in federated learning systems for medical imaging diagnostics. They discovered sparse representation as a potential solution to optimize urban air mobility routing.