RN-SLRA is a geometry-adaptive regularized Newton method for manifold-affine intersections that guarantees local linear convergence under intrinsic transversality and quadratic convergence under transversality with residual-dependent regularization.
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2 Pith papers cite this work. Polarity classification is still indexing.
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The no-barber principle prohibits selection rules in the inaccessible game that appeal to external adjudicators, favoring the symmetric monoidal category NCFinProb over the cartesian FinProb as its internal language due to the absence of canonical copying maps.
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The No Barber Principle: Towards Formalised Selection in the Inaccessible Game
The no-barber principle prohibits selection rules in the inaccessible game that appeal to external adjudicators, favoring the symmetric monoidal category NCFinProb over the cartesian FinProb as its internal language due to the absence of canonical copying maps.