Choosing the forcing terms in an inexact Newton method
SIAM Journal on Scientific Computing - Special issue on iterative methods in numerical linear algebra; selected papers from the Colorado conference
Matrix computations (3rd ed.)
Stability and Convergence of Principal Component Learning Algorithms
SIAM Journal on Matrix Analysis and Applications
The Geometry of Algorithms with Orthogonality Constraints
SIAM Journal on Matrix Analysis and Applications
Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
Trust Region Algorithms and Timestep Selection
SIAM Journal on Numerical Analysis
Adaptive Eigenvalue Computations Using Newton's Method on the Grassmann Manifold
SIAM Journal on Matrix Analysis and Applications
Cubically Convergent Iterations for Invariant Subspace Computation
SIAM Journal on Matrix Analysis and Applications
Pseudo-Transient Continuation for Nonsmooth Nonlinear Equations
SIAM Journal on Numerical Analysis
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
Optimization Algorithms on Matrix Manifolds
Optimization Algorithms on Matrix Manifolds
Modulated Hebb-Oja learning Rule-a method for principal subspace analysis
IEEE Transactions on Neural Networks
Riemannian Metric and Geometric Mean for Positive Semidefinite Matrices of Fixed Rank
SIAM Journal on Matrix Analysis and Applications
Low-Rank Optimization on the Cone of Positive Semidefinite Matrices
SIAM Journal on Optimization
A Riemannian Optimization Approach for Computing Low-Rank Solutions of Lyapunov Equations
SIAM Journal on Matrix Analysis and Applications
SIAM Journal on Matrix Analysis and Applications
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Newton's method for solving the matrix equation runs up against the fact that its zeros are not isolated. This is due to a symmetry of F by the action of the orthogonal group. We show how differential-geometric techniques can be exploited to remove this symmetry and obtain a “geometric” Newton algorithm that finds the zeros of F. The geometric Newton method does not suffer from the degeneracy issue that stands in the way of the original Newton method.