in this paper an approach based on evolutionary algorithms to find pareto optimal pair of state and control for multi-objective optimal control problems (moocp)'s is introduced‎. ‎in this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...

In this contribution we introduce a novel space-time formulation for non-linear elasticity, able to calculate large deformations and displacements with high efficiency using structured unstructured meshes in the cylinder without changing required regularity thus, enabling use of Lagrangian shape functions including tetrahedron hypertetrahedron or tesseract elements. The common indiscriminate tr...

We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large-scale feature selection problems. Identifying knockoff distribution requires solving semidefinite program for which we derive several efficient methods. One handles generic covariance matrices and has complexity scaling as $\mathcal{O}(p^3)$, where $p$ is ambient...

We consider the effect of parametric uncertainty on properties of Linear Time Invariant systems. Traditional approaches to this problem determine the worst-case gains of the system over the uncertainty set. Whilst such approaches are computationally tractable, the upper bound obtained is not necessarily informative in terms of assessing the influence of the parameters on the system performance....