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Trust-Region Methods on Riemannian Manifolds
TLDR
A general scheme for trust-region methods on Riemannian manifolds is proposed and analyzed, and particular attention is paid to the truncated conjugate-gradient technique.
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A Broyden Class of Quasi-Newton Methods for Riemannian Optimization
TLDR
A generalization of the Broyden class of quasi-Newton methods to the problem of minimizing a smooth objective function on a Riemannian manifold is developed and a condition on vector transport and retraction that guarantees convergence and facilitates efficient computation is derived.
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Asymptotic Waveform Evaluation via a Lanczos Method
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Parallel Algorithms for Dense Linear Algebra Computations
TLDR
The purpose is to review the current status and to provide an overall perspective of parallel algorithms for solving dense, banded, or block-structured problems arising in the major areas of direct solution of linear systems, least squares computations, eigenvalue and singular value computation, and rapid elliptic solvers.
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H2-optimal model reduction of MIMO systems
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Efficient algorithms for inferences on Grassmann manifolds
TLDR
This work defines and seeks an optimal linear representation using a Metropolis-Hastings type, stochastic search algorithm, and illustrates computation of sample statistics, such as mean and variances, on a Grassmann manifold for statistical inferences.
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The gSOAP Toolkit for Web Services and Peer-to-Peer Computing Networks
This paper presents the gSOAP stub and skeleton compiler. The compiler provides a unique SOAP-to-C/C++ language binding for deploying C/C++ applications in SOAP Web Services, clients, and…
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Model Reduction of MIMO Systems via Tangential Interpolation
TLDR
The resulting reduced order transfer function appears to be generically unique and this technique is a generalization of the multipoint Pade technique which is particularly suited to handle multiinput multioutput systems.
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A rational Lanczos algorithm for model reduction
TLDR
A variant of the nonsymmetric Lanczos method, rational Lanczos, is shown to yield a rational interpolant (multi-point Padé approximant) for the large-scale system.
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Joint Diagonalization on the Oblique Manifold for Independent Component Analysis
  • P. Absil, K. Gallivan
  • Computer Science
    IEEE International Conference on Acoustics Speech…
  • 14 May 2006
TLDR
It is shown how this indeterminacy can be taken into account by restricting the separating matrix to the oblique manifold by computing the congruence transformation that "best" diagonalizes a collection of covariance matrices.
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