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Two hidden layer suffice: the caterpillar net

Paper recorded by Signals 4 on 2026-10-19 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-19 on arXiv · recorded by Signals 4 on 2026-10-20

Category: cs.LG · 机器学习 · first seen 2026-10-20

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

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#241 most recent of 749 cs.LG papers we have recorded · ↑ newer: Teacher Supervision, Fixed Representations and Calibration: Exact Risk · ↓ older: On Data Scaling in Tabular ML: More Data, Better Generalization?
Cite this page: Two hidden layer suffice: the caterpillar net: the #241 most recent of 749 cs.LG papers we have recorded (as of 2026-10-19). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/two-hidden-layer-suffice-the-caterpillar-net.html
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