Search Results for author:
Found 4 papers, 0 papers with code
Symmetric Positive Semi-definite Riemannian Geometry with Application to Domain Adaptation
In this paper, we present new results on the Riemannian geometry of symmetric positive semi-definite (SPSD) matrices.
Spectral Discovery of Jointly Smooth Features for Multimodal Data
We show analytically that our method is guaranteed to provide a set of orthogonal functions that are as jointly smooth as possible, ordered by increasing Dirichlet energy from the smoothest to the least smooth.
Domain Adaptation with Optimal Transport on the Manifold of SPD matrices
We model the difference between two domains by a diffeomorphism and use the polar factorization theorem to claim that OT is indeed optimal for DA in a well-defined sense, up to a volume preserving map.
Local Canonical Correlation Analysis for Nonlinear Common Variables Discovery
In this paper, we address the problem of hidden common variables discovery from multimodal data sets of nonlinear high-dimensional observations.
