Riemannian statistics meets random matrix theory: towards learning from high-dimensional covariance matrices

1 March 2022

Papers citing "Riemannian statistics meets random matrix theory: towards learning from high-dimensional covariance matrices"

5 / 5 papers shown

Title
Invariant kernels on the space of complex covariance matrices Cyrus Mostajeran Salem Said 37 1 0 28 Mar 2024
Invariant kernels on Riemannian symmetric spaces: a harmonic-analytic approach Nathael Da Costa Cyrus Mostajeran Juan-Pablo Ortega Salem Said 32 4 0 30 Oct 2023
Geometric Learning with Positively Decomposable Kernels Nathael Da Costa Cyrus Mostajeran Juan-Pablo Ortega Salem Said 24 3 0 20 Oct 2023
Differential geometry with extreme eigenvalues in the positive semidefinite cone Cyrus Mostajeran Nathael Da Costa Graham W. Van Goffrier R. Sepulchre 27 4 0 14 Apr 2023
Geometric Learning of Hidden Markov Models via a Method of Moments Algorithm Berlin Chen Cyrus Mostajeran Salem Said 22 2 0 02 Jul 2022