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Research questionHow can size-constrained min-cut clustering efficiently enforce double-bounded constraints without producing trivial partitions?Size constraints complicate min-cut clustering because feasible partitions must balance graph-cut objectives with lower and upper limits on cluster sizes. Optimization procedures can be slow or settle on uninformative partitions.
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Latest papersRecent research connected to this question, newest first.Double-Bounded Nonlinear Optimal Transport for Size Constrained Min Cut ClusterinThe source formulates size-constrained min-cut clustering as a double-bounded nonlinear optimal transport problem and applies a Frank–Wolfe-based solver. It proves an O(1/t) convergence rate for convex, Lipschitz-smooth cases and reports results on eight benchmark datasets, where performance is competitive with the compared baselines.research paper · Sep 2, 2026
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