Efficient and Accurate Estimation of Lipschitz Constants for Hybrid Quantum-Classical Decision Models

• URL: http://arxiv.org/abs/2503.07992v1
• Date: Tue, 11 Mar 2025 02:50:16 GMT
• Title: Efficient and Accurate Estimation of Lipschitz Constants for Hybrid Quantum-Classical Decision Models
• Authors: Sajjad Hashemian, Mohammad Saeed Arvenaghi,
• Abstract summary: We propose a novel framework for efficiently and accurately estimating Lipschitz constants in hybrid quantum-classical decision models.<n>Our approach integrates classical neural network with quantum variational circuits to address critical issues in learning theory.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: In this paper, we propose a novel framework for efficiently and accurately estimating Lipschitz constants in hybrid quantum-classical decision models. Our approach integrates classical neural network with quantum variational circuits to address critical issues in learning theory such as fairness verification, robust training, and generalization. By a unified convex optimization formulation, we extend existing classical methods to capture the interplay between classical and quantum layers. This integrated strategy not only provide a tight bound on the Lipschitz constant but also improves computational efficiency with respect to the previous methods.

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