14 citations · 58 across the 16 of their papers we have counts for
3 papers · 1 filter
Gaussian distributions on Riemannian symmetric spaces: statistical learning with structured covariance matrices
Salem Said, Hatem Hajri, Lionel Bombrun +1
The Riemannian geometry of covariance matrices has been essential to several successful applications, in computer vision, biomedical signal and image processing, and radar data pro…
An information theoretic formulation of the Dictionary Learning and Sparse Coding Problems on Statistical Manifolds
Rudrasis Chakraborty, Monami Banerjee, Victoria Crawford +1
In this work, we propose a novel information theoretic framework for dictionary learning (DL) and sparse coding (SC) on a statistical manifold (the manifold of probability distribu…
An efficient Exact-PGA algorithm for constant curvature manifolds
Rudrasis Chakraborty, Dohyung Seo, Baba C. Vemuri
Manifold-valued datasets are widely encountered in many computer vision tasks. A non-linear analog of the PCA, called the Principal Geodesic Analysis (PGA) suited for data lying on…