Low-rank matrix completion is the task of recovering unknown entries of ...
Orthogonality constraints naturally appear in many machine learning prob...
We consider the problem of minimizing a differentiable function with loc...
We consider the problem of minimizing a differentiable function with loc...
We compare two first-order low-rank optimization algorithms, namely
P^2G...
Tangent and normal cones play an important role in constrained optimizat...
We consider the problem of minimizing a differentiable function with loc...
The Grassmann manifold of linear subspaces is important for the mathemat...
We consider a low-rank tensor completion (LRTC) problem which aims to re...
We propose the SH model, a simplified version of the well-known SIR
comp...
We propose a differential geometric construction for families of low-ran...
This paper concerns the minimax center of a collection of linear subspac...
Invariance transformations of polyadic decompositions of matrix
multipli...
We present a method to compute a fitting curve B to a set of data points...
The third edition of the "international - Traveling Workshop on Interact...
The implicit objective of the biennial "international - Traveling Worksh...
Optimization on manifolds is a rapidly developing branch of nonlinear
op...