Adaptive Newton-CG methods achieve the best-known iteration complexity for epsilon-stationary points in nonconvex optimization with Holder continuous Hessians while ensuring local superlinear convergence.
Mishchenko, ‘‘Regularized Newton method with globalO 1 k 2 convergence,’’SIAM Journal on Optimization, vol
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Adaptive Newton-CG methods achieve the best-known iteration complexity for epsilon-stationary points in nonconvex optimization with Holder continuous Hessians while ensuring local superlinear convergence.
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