Optimal-Control Method Adapts Network Depth With A-Posteriori Error Bounds

arXiv·low signal

This paper frames neural-network architecture adaptation as an optimal-control problem, adjusting depth using a-posteriori error estimation. It is a theory-forward contribution toward principled, error-aware architecture search, with practical payoff still to be demonstrated at scale.