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math.OC2026
Riemannian optimization with finite-difference gradient approximations
Timothé Taminiau, Estelle Massart, Geovani Nunes Grapiglia
Derivative-free Riemannian optimization (DFRO) aims to minimize an objective function using only function evaluations, under the constraint that the decision variables lie on a Rie…
math.OC2025
Enhancing finite-difference based derivative-free optimization methods with machine learning
Timothé Taminiau, Estelle Massart, Geovani Nunes Grapiglia
Derivative-Free Optimization (DFO) involves methods that rely solely on evaluations of the objective function. One of the earliest strategies for designing DFO methods is to adapt…