145 citations · 303 across the 28 of their papers we have counts for
4 papers · 1 filter
Robust Structured Low-Rank Approximation on the Grassmannian
Clemens Hage, Martin Kleinsteuber
Over the past years Robust PCA has been established as a standard tool for reliable low-rank approximation of matrices in the presence of outliers. Recently, the Robust PCA approac…
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…
Robust PCA and subspace tracking from incomplete observations using L0-surrogates
Clemens Hage, Martin Kleinsteuber
Many applications in data analysis rely on the decomposition of a data matrix into a low-rank and a sparse component. Existing methods that tackle this task use the nuclear norm an…