Quantum gradient descent and Newton’s method for constrained polynomial optimization

Optimization problems in disciplines such as machine learning are commonly solved with iterative methods. Gradient descent algorithms find local minima by moving along the direction of steepest descent while Newton’s method takes into account curvature information and thereby often improves converge...

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Bibliographic Details
Main Authors: Patrick Rebentrost, Maria Schuld, Leonard Wossnig, Francesco Petruccione, Seth Lloyd
Format: Article
Language:English
Published: IOP Publishing 2019-01-01
Series:New Journal of Physics
Subjects:
Online Access:https://doi.org/10.1088/1367-2630/ab2a9e