Low-Rank Models and Applications (LRMA 22)
15-16 september 2022
Project COLORAMAP, een ERC-project, en project SeLMA, een EOS-project (met de steun van FWO en FNRS)
The workshop will focus on the use of low-rank models in signal processing, data mining and machine learning.
This includes but is not restricted to all aspects of low-rank matrix/tensor approximations, such as nonnegative matrix factorization, (subspace) clustering, independent component analysis, low-rank matrix completion, sparse component analysis, dictionary learning, tensor decompositions, etc. The workshop is also interested in optimization algorithms that are central to compute such decompositions. Many aspects of this class of problems will be discussed including theory (complexity, identifiability, etc.), algorithms, and applications.