Optimization on the Oblique Manifold for Sparse Simplex Constraints via Multiplicative Updates
This work addresses low-rank optimization problems with sparse simplex constraints using a novel manifold approach. It reformulates these complex problems onto an oblique manifold, allowing for efficient solving via a method called Riemannian Multiplicative Update (RMU). This method incorporates the simplex constraints directly into the optimization steps, leading to faster convergence and better performance than standard methods.