Which mathematical concept is NOT typically used in modern retail personalization algorithms?

Personalization algorithms have revolutionized how retailers connect products with consumers. Behind these sophisticated systems lie complex mathematical concepts that power recommendation engines, predict consumer behavior, and optimize product offerings. This trivia question explores the mathematical foundation that enables retailers to deliver customized shopping experiences at scale.

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Bayesian probability for predicting customer preferences
Quantum computing for real-time recommendation calculations
Matrix factorization for collaborative filtering systems
Gradient descent for optimizing personalization models