Dominik Stöger
Cited by
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Blind demixing and deconvolution at near-optimal rate
P Jung, F Krahmer, D Stöger
IEEE Transactions on Information Theory 64 (2), 704-727, 2017
Blind deconvolution and compressed sensing
D Stöger, P Jung, F Krahmer
2016 4th International Workshop on Compressed Sensing Theory and its …, 2016
On the convex geometry of blind deconvolution and matrix completion
F Krahmer, D Stöger
arXiv preprint arXiv:1902.11156, 2019
Refined performance guarantees for sparse power factorization
JA Geppert, F Krahmer, D Stöger
2017 International Conference on Sampling Theory and Applications (SampTA …, 2017
Sparse Power Factorization: Balancing peakiness and sample complexity
J Geppert, F Krahmer, D Stöger
Advances in Computational Mathematics 45 (3), 1711-1728, 2019
Blind demixing and deconvolution with noisy data: Near-optimal rate
D Stöger, P Jung, F Krahmer
WSA 2017; 21th International ITG Workshop on Smart Antennas, 1-5, 2017
Blind Demixing and Deconvolution with Noisy Data: Near-optimal Rate
P Jung, F Krahmer, D Stoeger
WSA 2017; 21th International ITG Workshop on Smart Antennas; Proceedings of, 1-5, 2017
Complex phase retrieval from subgaussian measurements
F Krahmer, D Stöger
Journal of Fourier Analysis and Applications 26 (6), 1-27, 2020
Rigidity for perimeter inequality under spherical symmetrisation
F Cagnetti, M Perugini, D Stöger
Calculus of Variations and Partial Differential Equations 59 (4), 1-53, 2020
Blind Deconvolution: Convex Geometry and Noise Robustness
F Krahmer, D Stöger
2018 52nd Asilomar Conference on Signals, Systems, and Computers, 643-646, 2018
Sparse power factorization with refined peakiness conditions
D Stöger, J Geppert, F Krahmer
2018 IEEE Statistical Signal Processing Workshop (SSP), 816-820, 2018
Bilinear Compressed Sensing
D Stöger
Technische Universität München, 2019
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