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Uniqueness of a solution is guaranteed under analogous Carathéodory ordinary-differential equation uniqueness assumptions.
Hence a first-best solution is guaranteed without moral hazard issue.
The main advantage of the method comes from the fact that an integer solution is guaranteed.
The Beltrami equation is obtained using Harmonic map theory, and therefore the existence and uniqueness of a solution is guaranteed.
Stability of the solution is guaranteed by constraints that ensure a minimal distance between the nominal operating point and a stability boundary in the space of uncertain parameters.
The proposed approach is subsequently extended to evaluate the maximum guaranteed distance to uncontrollability of a system through a quasi-convex optimization problem whose solution is guaranteed to be globally optimal.
We follow an approach to data analytics where the computational complexity is fundamentally reduced by performing the majority of the computation in an approximated or even stochastic framework while the high precision solution is guaranteed by an iterative refinement process.
Hence, the feasibility of the new solution is guaranteed.
However, the unique solution is guaranteed only when the cost function is convex.
In both cases, the existence of a solution is guaranteed from a monotone iterative technique.
The strong convergence for the proposed algorithm to the solution is guaranteed under some assumptions.
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