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math.OC2026
Gray-Box Optimization using Optimism in the Face of Uncertainty
Katrin Baumgärtner, Léo Simpson, Moritz Diehl
This paper considers sequential gray-box optimization where the objective function is given as the composition of a loss function and a parametric model. Crucially, the parameters…
math.OC2026
Anderson Acceleration for Linearly Converging SQP-Type Methods
Jonathan Frey, David Kiessling, Katrin Baumgärtner +1
Although Anderson acceleration (AA) is known to speed up fixed-point iterations, it is rarely applied in constrained optimization, in particular sequential quadratic programming (S…