Sectional curvatures in nonlinear optimization

The aim of the paper is to show how to explicitly express the function of sectional curvature with the first and second derivatives of the problem’s functions in the case of submanifolds determined by equality constraints in the n-dimensional Euclidean space endowed with the induced Riemannian metric, which is followed by the formulation of the minimization problem of sectional curvature at an arbitrary point of the given submanifold as a global minimization one on a Stiefel manifold. Based on the results, the sectional curvatures of Stiefel manifolds are analysed and the maximal and minimal sectional curvatures on an ellipsoid are determined. This research was supported in part by the Hungarian Scientific Research Fund, Grant No. OTKA-T043276 and OTKA-K60480.     

Morse�CBott functions and the Lusternik�CSchnirelmann category

Lusternik–Schnirelmann category of a manifold gives a lower bound of the number of critical points of a differentiable map on it. The purpose of this paper is to show how to construct cone-decompositions of manifolds by using functions of class C ¹ and their gradient flows, where cone-decompositions are used to give an upper bound for the Lusternik–Schnirelmann category which is a homotopy invariant of a topological space. In particular, the Morse–Bott functions on the Stiefel manifolds considered by Frankel (1965) are effectively used to construct the conedecompositions of Stiefel manifolds and symmetric Riemannian spaces to determine their Lusternik–Schnirelmann categories.     

Stiefel流形上的梯度下降法

基于Stiefel流形上算法的几何框架,本文提出了Stiefel流形上的梯度下降法.理论上给出了算法收敛性定理.三个数值仿真算例表明算法是有效的,与其他方法相比具有更快的收敛速度.     

The Mitchell-Richter filtration of loops on Stiefel manifolds stably splits

We prove that the Mitchell-Richter filtration of the space of loops on complex Stiefel manifolds stably splits. The result is obtained as a special case of a more general splitting theorem. Another special case is H. Miller's splitting of Stiefel manifolds. The proof uses the theory of orthogonal calculus developed by M. Weiss. The argument is inspired by an old argument of Goodwillie for a different, but closely related, general splitting result.

     

Well-posedness of convex maximization problems on Stiefel manifolds and orthogonal tensor product approximations

Problems of best tensor product approximation of low orthogonal rank can be formulated as maximization problems on Stiefel manifolds. The functionals that appear are convex and weakly sequentially continuous. It is shown that such problems are always well-posed, even in the case of non-compact Stiefel manifolds. As a consequence, problems of finding a best orthogonal, strong orthogonal or complete orthogonal low-rank tensor product approximation and problems of best Tucker format approximation to any given tensor are always well-posed, even in spaces of infinite dimension. (The best rank-one approximation is a special case of all of them.) In addition, the well-posedness of a canonical low-rank approximation with bounded coefficients can be shown. The proofs are non-constructive and the problem of computation is not addressed here.     

Nonmonotone algorithm for minimization on closed sets with applications to minimization on Stiefel manifolds

A nonmonotone Levenberg–Marquardt-based algorithm is proposed for minimization problems on closed domains. By preserving the feasible set’s geometry throughout the process, the method generates a feasible sequence converging to a stationary point independently of the initial guess. As an application, a specific algorithm is derived for minimization on Stiefel manifolds and numerical results involving a weighted orthogonal Procrustes problem are reported.     

State space models on special manifolds

This paper concerns modeling time series observations in state space forms considered on the Stiefel and Grassmann manifolds. We develop a state space model relating the time series observations to a sequence of unobserved state or parameter matrices assuming the matrix Langevin noise processes on the Stiefel manifolds. We show a Bayes method for estimating the state matrices by the posterior modes. We consider a further extended state space model where two sequences of unobserved state matrices are involved. A simple state space model on the Grassmann manifolds with matrix Langevin noise processes is also investigated.     

A matrix-free implementation of Riemannian Newton’s method on the Stiefel manifold

Newton’s method for unconstrained optimization problems on the Euclidean space can be generalized to that on Riemannian manifolds. The truncated singular value problem is one particular problem defined on the product of two Stiefel manifolds, and an algorithm of the Riemannian Newton’s method for this problem has been designed. However, this algorithm is not easy to implement in its original form because the Newton equation is expressed by a system of matrix equations which is difficult to solve directly. In the present paper, we propose an effective implementation of the Newton algorithm. A matrix-free Krylov subspace method is used to solve a symmetric linear system into which the Newton equation is rewritten. The presented approach can be used on other problems as well. Numerical experiments demonstrate that the proposed method is effective for the above optimization problem.     

Properly discontinuous actions on Hilbert manifolds

In this article we study properly discontinuous actions on Hilbert manifolds giving new examples of complete Hilbert manifolds with nonnegative, respectively nonpositive, sectional curvature with infinite fundamental group. We also get examples of complete infinite dimensional Kähler manifolds with positive holomorphic sectional curvature and infinite fundamental group in contrastwith the finite dimensional case and we classify abelian groups acting linearly, isometrically and properly discontinuously on Stiefel manifolds. Finally, we classify homogeneous Hilbert manifolds with constant sectional curvature.     

Some optimization problems in multivariate statistics

Interesting and important multivariate statistical problems containing principal component analysis, statistical visualization and singular value decomposition, furthermore, one of the basic theorems of linear algebra, the matrix spectral theorem, the characterization of the structural stability of dynamical systems and many others lead to a new class of global optimization problems where the question is to find optimal orthogonal matrices. A special class is where the problem consists in finding, for any 2kn, the dominant k-dimensional eigenspace of an n×n symmetric matrix A in R ⁿ where the eigenspaces are spanned by the k largest eigenvectors. This leads to the maximization of a special quadratic function on the Stiefel manifold M _n,k . Based on the global Lagrange multiplier rule developed in Rapcsák (1997) and the paper dealing with Stiefel manifolds in optimization theory (Rapcsák, 2002), the global optimality conditions of this smooth optimization problem are obtained, then they are applied in concrete cases.     

Closed-form Geodesics and Optimization for Riemannian Logarithms of Stiefel and Flag Manifolds

Journal of Optimization Theory and Applications - We provide two closed-form geodesic formulas for a family of metrics on Stiefel manifolds recently introduced by Hüper, Markina and Silva...     

On the Stiefel-Baumgarte stabilization procedure

The purpose of this paper is to justify a stabilization procedure for ordinary differential equations due to Stiefel and Baumgarte. The main tools are methods and results from the theory of invariant manifolds of dynamical systems.

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Zusammenfassung In dieser Arbeit wird ein von Stiefel und Baumgarte vorgeschlagenes Verfahren zur Stabilisierung von gewöhnlichen Differentialgleichungen theoretisch begründet. Als Hilfsmittel verwenden wir Methoden und Resultate aus der Theorie der invarianten Mannigfaltigkeiten dynamischer Systeme.

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To the memory of Professor E. Stiefel     

Parallelizability of complex projective Stiefel manifolds

The question of parallelizability of the complex projective Stiefel manifolds is settled.

     

On the Lusternik-Schnirelmann category of Stiefel manifolds

We determine the Lusternik-Schnirelmann category of real Stiefel manifolds Vn,k and quaternionic Stiefel manifolds Xn,k for n?2k which is equal to the cup-length of the mod 2 cohomology of Vn,k and the integer cohomology of Xn,k, respectively.     

Almost complex and complex structures on real projective Stiefel manifolds

We give a complete list of real projective Stiefel manifolds which admit almost complex structures and show that many of them are in fact complex manifolds. The first named author was supported in part by Grants 1/1486/94 and 2/1225/96 of VEGA (Slovakia) during the preparation of this work.     

A Procrustes problem on the Stiefel manifold

Summary. An orthogonal Procrustes problem on the Stiefel manifold is studied, where a matrix Q with orthonormal columns is to be found that minimizes for an matrix A and an matrix B with and . Based on the normal and secular equations and the properties of the Stiefel manifold, necessary conditions for a global minimum, as well as necessary and sufficient conditions for a local minimum, are derived. Received April 7, 1997 / Revised version received April 16, 1998     

Real, complex and quaternionic equivariant vector fields on spheres

The equivariant real, complex and quaternionic vector fields on spheres problem is reduced to a question about the equivariant J-groups of the projective spaces. As an application of this reduction, we give a generalization of the results of Namboodiri [U. Namboodiri, Equivariant vector fields on spheres, Trans. Amer. Math. Soc. 278 (2) (1983) 431-460], on equivariant real vector fields, and Önder [T. Önder, Equivariant cross sections of complex Stiefel manifolds, Topology Appl. 109 (2001) 107-125], on equivariant complex vector fields, which avoids the restriction that the representation containing the sphere has enough orbit types.     

On a sub‐Stiefel Procrustes problem arising in computer vision

A sub‐Stiefel matrix is a matrix that results from deleting simultaneously the last row and the last column of an orthogonal matrix. In this paper, we consider a Procrustes problem on the set of sub‐Stiefel matrices of order n. For n = 2, this problem has arisen in computer vision to solve the surface unfolding problem considered by R. Fereirra, J. Xavier and J. Costeira. An iterative algorithm for computing the solution of the sub‐Stiefel Procrustes problem for an arbitrary n is proposed, and some numerical experiments are carried out to illustrate its performance. For these purposes, we investigate the properties of sub‐Stiefel matrices. In particular, we derive two necessary and sufficient conditions for a matrix to be sub‐Stiefel. We also relate the sub‐Stiefel Procrustes problem with the Stiefel Procrustes problem and compare it with the orthogonal Procrustes problem. Copyright © 2015 John Wiley & Sons, Ltd.     

On the equivariant cohomology of rotation groups and Stiefel manifolds

In this paper, we compute the RO(Z/2)-graded equivariant cohomology of rotation groups and Stiefel manifolds with particular involutions.