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The role of locality and weight sharing in convolutional neural networks

Paper recorded by Signals 4 on 2026-10-21 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-21 on arXiv · recorded by Signals 4 on 2026-10-22

Category: cs.LG · 机器学习 · first seen 2026-10-22

Abstract

The success of convolutional neural networks is often attributed to locality and weight sharing. However, how these two properties separately shape learning, and how their effects depend on the spatial correlations of natural images, remain poorly understood. We address these questions in a teacher-student model with a convolutional teacher acting on $P$ input positions with correlation $c$ betwee

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#207 most recent of 749 cs.LG papers we have recorded · ↑ newer: Self-normalized Bernstein Inequalities for Regenerative Processes and · ↓ older: Minimax Optimality of the NPMLE for Gaussian Mixtures in Hellinger Dis
Cite this page: The role of locality and weight sharing in convolutional neural networks: the #207 most recent of 749 cs.LG papers we have recorded (as of 2026-10-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/the-role-of-locality-and-weight-sharing-in-convolutional-neural-networks.html
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