AI RESEARCH
A Deep State-Space Model Compression Method using Upper Bound on Output Error
arXiv CS.LG
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ArXi:2510.14542v2 Announce Type: replace-cross We study deep state-space models (Deep SSMs) that contain linear quadratic-output (LQO) systems as internal blocks and present a compression method with a provable output error guarantee. We first derive an upper bound on the output error between two Deep SSMs and show that the bound can be expressed in terms of the $h^2$-error norms between the layerwise LQO systems.