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International Journal of Robust and Nonlinear Control, 2023
SummaryWe introduce arisk‐sensitivegeneralization of the mixed control problem for linear stochastic systems with additive noise. Two criteria ofexponential‐quadraticform are used to generalise the usual quadratic criteria. The solutions are found in a linear state‐feedback form for both the finite and the infinite horizon formulations in terms of ...
Haochen Hua, Bujar Gashi, Moyu Zhang
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SummaryWe introduce arisk‐sensitivegeneralization of the mixed control problem for linear stochastic systems with additive noise. Two criteria ofexponential‐quadraticform are used to generalise the usual quadratic criteria. The solutions are found in a linear state‐feedback form for both the finite and the infinite horizon formulations in terms of ...
Haochen Hua, Bujar Gashi, Moyu Zhang
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Neural Predictors’ Sensitivity and Robustness
2021The results of the application of deep neural predictors depend on a multitude of factors which compose the experimental settings. We report all the specific information to ensure the reproducibility of a wide number of numerical experiments. A sensitivity analysis on some critical aspects is provided in order to prove the robustness of our setting ...
M. Sangiorgio, F. Dercole, G. Guariso
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Robust SVM for Cost-Sensitive Learning
Neural Processing Letters, 2021Although the performance of cost-sensitive support vector machine (CS-SVM) has been demonstrated to approximate to the cost-sensitive Bayes risk, previous CS-SVM methods still suffer from the influence of outlier samples and redundant features. Recently, a few studies have focused on separately solving these two issues by the sparse theory.
Jiangzhang Gan +2 more
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