Abstract:
The language for AMs matured in the field of physics, but the fundamental concepts have also been studied in classical ML theory. This section bridges these disciplines by reframing modern AM theory through the lens of classical machine learning techniques, showing how principles from statistical learning, optimization theory, and neural networks provide fresh insights into AM systems.
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