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Exactness Conditions for a Convex Differentiable Exterior Penalty for Linear Programming
Sufficient conditions are given for a classical dual exterior penalty function of a linear program to be independent of its penalty parameter. This ensures that an exact solution to the primal linear program can be obtained ...
Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entities. Each entity is unwilling to share its ...
Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels
We propose a novel privacy-preserving nonlinear support vector machine (SVM) classifier for a data matrix A whose columns represent input space features and whose individual rows are divided into groups of rows. Each ...