Speaker
Zhengkang (Kevin) Zhang
Description
I will present the full solution to the random feature model recently proposed by Maloney, Roberts and Sully as a simplified model that exhibits neural scaling laws, extending the results in the latter reference beyond the ridgeless limit. The calculation is based on a new large-N diagrammatic method for all-order resummation. The result enables full predictions of scaling law exponents and also provides analytical understanding of the optimization of the ridge parameter.
