Nonlinear preconditioning extends Newton methods to objectives lacking Hessian Lipschitz continuity by analyzing a transformed mapping under a relaxed smoothness condition, with superlinear convergence and O(ε^{-3/2}) iteration complexity.
Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization
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Newton methods beyond Hessian Lipschitz continuity: A nonlinear preconditioning approach
Nonlinear preconditioning extends Newton methods to objectives lacking Hessian Lipschitz continuity by analyzing a transformed mapping under a relaxed smoothness condition, with superlinear convergence and O(ε^{-3/2}) iteration complexity.