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Matthias Seibert
Matthias Seibert
Doctoral Candidate at the Professorship for Geometric Optimization and Machine Learning at TUM
Verified email at tum.de
Title
Cited by
Cited by
Year
Separable dictionary learning
S Hawe, M Seibert, M Kleinsteuber
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
1342013
Sample complexity of dictionary learning and other matrix factorizations
R Gribonval, R Jenatton, F Bach, M Kleinsteuber, M Seibert
IEEE Transactions on Information Theory 61 (6), 3469-3486, 2015
942015
Learning co-sparse analysis operators with separable structures
M Seibert, J Wörmann, R Gribonval, M Kleinsteuber
IEEE Transactions on Signal Processing 64 (1), 120-130, 2015
232015
Properties of the BFGS method on Riemannian manifolds
M Seibert, M Kleinsteuber, K Hüper
Mathematical System Theory C Festschrift in Honor of Uwe Helmke on the …, 2013
132013
Separable cosparse analysis operator learning
M Seibert, J Wörmann, R Gribonval, M Kleinsteuber
2014 22nd European Signal Processing Conference (EUSIPCO), 770-774, 2014
102014
On the sample complexity of sparse dictionary learning
M Seibert, M Kleinsteuber, R Gribonval, R Jenatton, F Bach
2014 IEEE Workshop on Statistical Signal Processing (SSP), 244-247, 2014
32014
Sample Complexity of Representation Learning for Sparse and Related Data Models
M Seibert
Technische Universität München, 2019
22019
On the Sample Complexity of Analysis Operator Learning
M Seibert, M Kleinsteuber
Proceedings of SPARS 2015, 2015
2015
Apprentissage de dictionnaire pour les représentations parcimonieuses
R Gribonval, R Jenatton, F Bach, M Kleinsteuber, M Seibert
46e Journées de Statistique, 2014
2014
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