16 citations · 24 across the 4 of their papers we have counts for
4 papers
Separable Cosparse Analysis Operator Learning
Matthias Seibert, Julian Wörmann, Rémi Gribonval +1
The ability of having a sparse representation for a certain class of signals has many applications in data analysis, image processing, and other research fields. Among sparse repre…
On The Sample Complexity of Sparse Dictionary Learning
Matthias Seibert, Martin Kleinsteuber, Rémi Gribonval +2
In the synthesis model signals are represented as a sparse combinations of atoms from a dictionary. Dictionary learning describes the acquisition process of the underlying dictiona…
Sample Complexity of Dictionary Learning and other Matrix Factorizations
Rémi Gribonval, Rodolphe Jenatton, Francis Bach +2
Many modern tools in machine learning and signal processing, such as sparse dictionary learning, principal component analysis (PCA), non-negative matrix factorization (NMF), -me…
Separable Dictionary Learning
Simon Hawe, Matthias Seibert, Martin Kleinsteuber
Many techniques in computer vision, machine learning, and statistics rely on the fact that a signal of interest admits a sparse representation over some dictionary. Dictionaries ar…