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arXiv · 2504.00885

Spectral Architecture Search for Neural Network Models

Gianluca Peri·Lorenzo Chicchi·Duccio Fanelli·Lorenzo Giambagli
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Abstract

Architecture design and optimization are challenging problems in the field of artificial neural networks. Working in this context, we here present SPARCS (SPectral ARchiteCture Search), a novel architecture search protocol which exploits the spectral attributes of the inter-layer transfer matrices. SPARCS allows one to explore the space of possible architectures by spanning continuous and differentiable manifolds, thus enabling for gradient-based optimization algorithms to be eventually employed. With reference to simple benchmark models, we show that the newly proposed method yields a self-emerging architecture with a minimal degree of expressivity to handle the task under investigation and with a reduced parameter count as compared to other viable alternatives.

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Gianluca Peri, Lorenzo Chicchi, Duccio Fanelli, Lorenzo Giambagli. 2025-04-01. Spectral Architecture Search for Neural Network Models. https://arxiv.org/abs/2504.00885

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