Two hidden layer suffice: the caterpillar net
Abstract
Every continuous piecewise linear (CPWL) function is a finite signed sum of maxima of affine functions, making maximum representation a central problem in the study of the expressiveness of ReLU networks. A now-disproved conjecture predicted logarithmic depth for maxima. Inspired by the proof by Brunck et al. (2026) that two hidden layers suffice for general CPWL functions, we give the Caterpillar Net, a nonrecursive construction for the maximum of $N$ inputs with two hidden layers of widths $O(...
Description / Details
Every continuous piecewise linear (CPWL) function is a finite signed sum of maxima of affine functions, making maximum representation a central problem in the study of the expressiveness of ReLU networks. A now-disproved conjecture predicted logarithmic depth for maxima. Inspired by the proof by Brunck et al. (2026) that two hidden layers suffice for general CPWL functions, we give the Caterpillar Net, a nonrecursive construction for the maximum of inputs with two hidden layers of widths and . The construction has a direct geometric interpretation.
Source: arXiv:2610.26795v1 - http://arxiv.org/abs/2610.26795v1 PDF: https://arxiv.org/pdf/2610.26795v1 Original Link: http://arxiv.org/abs/2610.26795v1
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Oct 20, 2026
Data Science
Machine Learning
0