Tag: stochastic optimization

ScientificML

Proposes a Bayesian decision-theoretic framework for multiobjective optimization under uncertainties, maximizing the expected hypervolume with respect to input points using gradient-based stochastic optimization.

Quantum/Chemistry

A spectral co-design framework that directly couples fabrication-constrained SPSA-Adam optimizer with full-wave finite-element eigenmode simulations for multifrequency Rydberg electrometry, operating without analytical or adjoint gradients.