Learning and Regression on manifolds: Data on Grassmannian manifolds
Published in PR International Conference on Artificial Intelligence, Jakarta, Indonesia, November 15-19, 2023, 2023
Recommended citation: Anis Fradi, Chafik Samir, PRICAI 2023. https://doi.org/10.1007/978-981-99-7022-3\_6
In this paper, we introduce a new method for learning and regression from a finite set of noisy points on Grassmann manifolds. In contrast to previously existing methods, we propose a new Riemannian Monte Carlo method to sample from the posterior distribution of the tangent space of a Grassmann manifold. Specifically, we investigate and exploit the geometric structure of this manifold which can be used as a solid basis to extend the proposed method to other manifolds in a similar manner. We demonstrate our method for regression using different setups and datasets.