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The state-of-the art algorithms for this problem are based on spectral clustering techniques.
It is worth mentioning that almost all the existing algorithms for this problem are based on the proximal point method applied to the equilibrium problem combining with a Mann iteration to fixed point problems of nonexpansive mappings, of which the convergence analysis has been considered if the bifunction F is monotone.
Most systematic approaches for this problem are based on individual segmentation of each sample followed by post-processing to combine results across samples (see, e.g., [ 18] and references therein), while some recent publications propose strategies for joint segmentation of all samples [ 19- 23].
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A promising approach for addressing this problem is based on characterizing the "most unstable" switching law.
This scheduling problem is NP-hard and solutions for large problems are based on non-exact methods.
The idea of solving m-stopping problem is based on the one for solving the one-stopping problem.
The method for solving the Riemann problem is based on the following results.
Mathematical formulation of the optimization problem is based on a straightforward approach typical for radio coverage problems.
However, the current mhGAP recommendations for treatment of child behavioural problems are based on limited data from LMIC patient populations.
Most problems are based on simulated data from a known source model, which is important for evaluation purposes.
Problems were based on a range of stereotypes (e.g., involving gender, age, nationality, see Appendix S1 for an overview).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com