We give simple formulas for the canonical metric, gradient, Lie derivative, Riemannian connection, parallel translation, geodesics and distance on the Grassmann manifold of p-planes in R-n. In these formulas, p-planes are represented as the column space of n x p matrices. The Newton method on abstract Riemannian manifolds proposed by Smith is made explicit on the Grassmann manifold. Two applications - computing an invariant subspace of a matrix and the mean of subspaces - are worked out
Several applications in optimization, image, and signal processing deal with data belonging to matri...
Abstract. The techniques and analysis presented in this paper provide new meth-ods to solve optimiza...
International audienceParallel transport on Riemannian manifolds allows one to connect tangent space...
We give simple formulas for the canonical metric, gradient, Lie derivative, Riemannian connection, p...
We give simple formulas for the canonical metric, gradient, Lie derivative, Riemannian connection, p...
Abstract—The squared distance function is one of the standard functions on which an optimization alg...
AbstractWe use a Hamiltonian approach and symplectic methods to compute the geodesics on a Riemannia...
peer reviewedWe consider two Riemannian geometries for the manifold M(p, m × n) of all m × n matric...
This thesis is devoted to geometric methods in optimization, learning and neural networks. In many p...
In recent years, optimisation on manifolds has become a popular area of research. Applications in si...
The classical Rayleigh Quotient Iteration (RQI) computes a 1-dimensional invariant subspace of a sym...
We provide an explicit formula for the Levi-Civita connection and Riemannian Hessian for a Riemannia...
International audienceParallel transport is a fundamental tool to perform statistics on Riemannian m...
The optimization of a real-valued objective function f(U), where U is a p X d,p > d, semi-orthogonal...
In this paper we developed a new Lanczos algorithm on the Grassmann manifold. This work comes in ...
Several applications in optimization, image, and signal processing deal with data belonging to matri...
Abstract. The techniques and analysis presented in this paper provide new meth-ods to solve optimiza...
International audienceParallel transport on Riemannian manifolds allows one to connect tangent space...
We give simple formulas for the canonical metric, gradient, Lie derivative, Riemannian connection, p...
We give simple formulas for the canonical metric, gradient, Lie derivative, Riemannian connection, p...
Abstract—The squared distance function is one of the standard functions on which an optimization alg...
AbstractWe use a Hamiltonian approach and symplectic methods to compute the geodesics on a Riemannia...
peer reviewedWe consider two Riemannian geometries for the manifold M(p, m × n) of all m × n matric...
This thesis is devoted to geometric methods in optimization, learning and neural networks. In many p...
In recent years, optimisation on manifolds has become a popular area of research. Applications in si...
The classical Rayleigh Quotient Iteration (RQI) computes a 1-dimensional invariant subspace of a sym...
We provide an explicit formula for the Levi-Civita connection and Riemannian Hessian for a Riemannia...
International audienceParallel transport is a fundamental tool to perform statistics on Riemannian m...
The optimization of a real-valued objective function f(U), where U is a p X d,p > d, semi-orthogonal...
In this paper we developed a new Lanczos algorithm on the Grassmann manifold. This work comes in ...
Several applications in optimization, image, and signal processing deal with data belonging to matri...
Abstract. The techniques and analysis presented in this paper provide new meth-ods to solve optimiza...
International audienceParallel transport on Riemannian manifolds allows one to connect tangent space...