KL-based Control of the Learning Schedule for Surrogate Black-Box Optimization
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Econometric models play an important role in transportation analysis. Estimating more and more complex models becomes problematic. The associated log-likelihood function is highly nonlinear and non concave and the comlexity of the model requires constraint ...
We propose new trust-region based optimization algorithms for solving unconstrained nonlinear problems whose second derivatives matrix is singular at a local solution. We give a theoretical characterization of the singularity in this context and we propose ...
Econometric models play an important role in transportation analysis. Estimating more and more complex models becomes problematic. The associated log-likelihood function is highly nonlinear and non concave and the comlexity of the model requires constraint ...
The aim of this paper is to present a global approach to dynamic optimization of batch emulsion polymerization reactors using a stochastic optimizer. The objective is to minimize the final batch time with constraints on the final conversion and molecular w ...
The Intelligent Grid Scheduling Service (ISS) aims at finding an optimally suited computational resource for a given application component. An objective cost model function is used to decide it. It includes information on a parametrization of the component ...