A mathematical method using swap distance in permutohedrons shows crosslinguistic gestures achieve at least 77% optimality, unlikely by chance, and unifies linguistic principles under optimal assignment.
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DCBM community detection is reformulated as constrained nonnegative matrix factorization, producing a scalable method with strong initialization that matches inference quality on large graphs.
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How to measure the optimality of word or gesture order with respect to the principle of swap distance minimization
A mathematical method using swap distance in permutohedrons shows crosslinguistic gestures achieve at least 77% optimality, unlikely by chance, and unifies linguistic principles under optimal assignment.
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Matrix Factorization Framework for Community Detection under the Degree-Corrected Block Model
DCBM community detection is reformulated as constrained nonnegative matrix factorization, producing a scalable method with strong initialization that matches inference quality on large graphs.