NP-Hardness of Minimizing Neurons in Two-Hidden-Layer ReLU Neural Networks
This research proves that finding the exact minimum number of hidden neurons required for a two-hidden-layer ReLU neural network is NP-hard. This means there is no efficient, guaranteed method to find the absolute smallest network structure for a given function approximation task, establishing a worst-case computational barrier.