Riemannian Trust Regions with Finite-Difference Hessian Approximations are Globally Convergent

DOI10.1007/978-3-319-25040-3_50zbMath1405.90124OpenAlexW2258202344MaRDI QIDQ2807547

Nicolas Boumal

Publication date: 25 May 2016

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-25040-3_50

zbMATH Keywords

convergenceoptimization on manifoldsManoptRTR-FD

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Related Items (6)

Riemannian stochastic variance-reduced cubic regularized Newton method for submanifold optimization ⋮ Riemannian Hamiltonian Methods for Min-Max Optimization on Manifolds ⋮ Unnamed Item ⋮ Nonlinearly Preconditioned Optimization on Grassmann Manifolds for Computing Approximate Tucker Tensor Decompositions ⋮ Intrinsic Formulation of KKT Conditions and Constraint Qualifications on Smooth Manifolds ⋮ The Condition Number of Riemannian Approximation Problems

Uses Software

• Manopt

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