GitHub repository: mostafakalhor/LocallyConvexRegions
Description: It is a machine learning algorithm to find the optimal and robust solution in an optimization problem with uncertainties. For this mean, the loss function (by using the given data samples) is approximated as a set of locally convex regions which are interpolated by Gaussian kernel functions. Such a model can be considered as a regression model, which is identified by a variant of the clustering-based support vector regression method. Actually, in this method, the convex regions are identified by a fast incremental clustering algorithm and then be analyzed by a singular value decomposition technique. The resulted local convex regions are used to find the optimal and robust solution for the problem