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arXiv:2503.07992 · v2

Certified Lipschitz Bounds for Hybrid Quantum-Classical Decision Models

首次提交 2025-03-11 10:50
版本更新 2026-11-07 06:55
雷达观测 2026-11-10 11:14
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摘要

We study certified upper bounds on Lipschitz constants for hybrid quantum-classical decision models, which combine classical neural-network layers with parameterized quantum circuits. We pair an SDP-based certificate for classical layers with an exact spectral characterization for probability-output quantum models. For hybrid architectures, these componentwise estimates are connected through the encoding maps to obtain a certified composition bound for the complete model. The resulting bounds support sensitivity analyses relevant to robustness, stability, generalization, and fairness.

作者备注:14 pages, 6 figuers, a previous version of this article is published in the 2025 Iranian International Artificial Intelligence Conference (ICAI)

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v2 · 2026-11-07 06:55 · 最新观测版本

Certified Lipschitz Bounds for Hybrid Quantum-Classical Decision Models

We study certified upper bounds on Lipschitz constants for hybrid quantum-classical decision models, which combine classical neural-network layers with parameterized quantum circuits. We pair an SDP-based certificate for classical layers with an exact spectral characterization for probability-output quantum models. For hybrid architectures, these componentwise estimates are connected through the encoding maps to obtain a certified composition bound for the complete model. The resulting bounds support sensitivity analyses relevant to robustness, stability, generalization, and fairness.

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