p-conductance learning solves an affine-relaxed p-norm mincut over diffused label measures, linking mincut, effective resistance, and Wasserstein distance, and reporting strong accuracy in low-label, corrupted-label, and partial-label graph classification.
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Robust Graph-Based Semi-Supervised Learning via $p$-Conductances
p-conductance learning solves an affine-relaxed p-norm mincut over diffused label measures, linking mincut, effective resistance, and Wasserstein distance, and reporting strong accuracy in low-label, corrupted-label, and partial-label graph classification.