Corpus ID: 221006687

Randomized Riemannian Preconditioning for Orthogonality Constrained Problems

@inproceedings{Shustin2019RandomizedRP,
  title={Randomized Riemannian Preconditioning for Orthogonality Constrained Problems},
  author={B. Shustin and H. Avron},
  year={2019}
}
  • B. Shustin, H. Avron
  • Published 2019
  • Mathematics, Computer Science
  • Optimization problems with (generalized) orthogonality constraints are prevalent across science and engineering. For example, in computational science they arise in the symmetric (generalized) eigenvalue problem, in nonlinear eigenvalue problems, and in electronic structures computations, to name a few problems. In statistics and machine learning, they arise, for example, in canonical correlation analysis and in linear discriminant analysis. In this article, we consider using randomized… CONTINUE READING

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 57 REFERENCES
    Manopt, a matlab toolbox for optimization on manifolds
    551
    The Geometry of Algorithms with Orthogonality Constraints
    2153
    Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold
    17
    The Gradient Projection Method Along Geodesics
    137
    Riemannian Preconditioning
    32
    LSRN: A Parallel Iterative Solver for Strongly Over- or Underdetermined Systems
    95