Models · Training · Optimization

Control-Informed Machine Learning

This direction uses ideas and viewpoints from control to study learning more broadly. Learning models, training procedures, and optimization algorithms can all be understood as dynamical processes, opening up new ways to reason about their stability, efficiency, convergence, and reliability.