The author presents a novel "Pareto-Laplace" integral transform framework for design optimization, offering insights into relationships between objectives and outcomes.
Integral transform framework for optimization problems.
Hybrid approach combining diagonal Hessian approximation and fuzzy logic for efficient optimization.
Line search methods are enhanced for large-scale neural network training, outperforming traditional approaches.
Optimization techniques can be enhanced by applying the Pareto-Laplace integral transform framework to gain new insights into design spaces.