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Given a complete graph Kn = (V, E) with edge weight ce on each edge, we consider the problem of partitioning the vertices of graph Kn into subcliques that have at least S vertices, so as to minimize the total weight of the edges that have both endpoints in the same subclique. In this paper, we consider using the branch-and-price method to solve the problem.(More)
A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be selected by the users. While cross validation is a commonly employed and widely accepted method for selecting these parameters, its implementation by a grid-search procedure in the(More)
The sports team realignment problem can be modelled as k-way equipartition: given a complete graph Kn = (V, E), with edge weight ce on each edge, partition the vertices V into k divisions that have exactly S vertices, so as to minimize the total weight of the edges that have both endpoints in the same division. In this paper, we discuss solving k-way(More)
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