Veröffentlichungen "Stöger, Dominik"

Kümmerle, Christian ; Stöger, Dominik:
Linear Convergence of Iteratively Reweighted Least Squares for Nuclear Norm Minimization.
In: 2024 IEEE 13rd Sensor Array and Multichannel Signal Processing Workshop (SAM). - Corvallis, OR, USA : IEEE, 2024
ISBN 979-8-3503-4481-3 ; 979-8-3503-4482-0
10.1109/SAM60225.2024.10636588
(Begutachteter Beitrag / peer-reviewed paper)

Soltanolkotabi, Mahdi ; Stöger, Dominik ; Xie, Changzhi:
Implicit Balancing and Regularization : Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing.
In: Proceedings of Machine Learning Research. 195 (2023). - S. 5140-5142.
ISSN 2640-3498
(Peer-Review-Journal)

Lee, Kiryung ; Stöger, Dominik:
Randomly Initialized Alternating Least Squares : Fast Convergence for Matrix Sensing.
In: SIAM Journal on Mathematics of Data Science. 5 (2023) 3. - S. 774-799.
ISSN 2577-0187
10.1137/22M1506456
(Peer-Review-Journal)

Ma, Anna ; Stöger, Dominik ; Zhu, Yizhe:
Robust Recovery of Low-Rank Matrices and Low-Tubal-Rank Tensors from Noisy Sketches.
In: SIAM journal on matrix analysis and applications / Society for Industrial and Applied Mathematics, SIAM. 44 (2023) 4. - S. 1566-1588.
ISSN 1095-7162
10.1137/22M150071X
(Peer-Review-Journal)

Fuchs, Tim ; Gross, David ; Jung, Peter ; Krahmer, Felix ; Kueng, Richard ; Stöger, Dominik:
Proof Methods for Robust Low-Rank Matrix Recovery.
In: Kutyniok, Gitta ; Rauhut, Holger ; Kunsch, Robert J. (Hrsg.): Compressed Sensing in Information Processing. - Cham : Birkhäuser, 2022. - S. 37-75. - (Applied and Numerical Harmonic Analysis)
ISBN 978-3-031-09744-7
ISSN 2296-5009
10.1007/978-3-031-09745-4_2
(Begutachteter Beitrag / peer-reviewed paper)

Stöger, Dominik ; Soltanolkotabi, Mahdi:
Small random initialization is akin to spectral learning : Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction.
In: Advances in Neural Information Processing Systems 34 (NeurIPS 2021). - 2021
(Begutachteter Beitrag / peer-reviewed paper)

Kümmerle, Christian ; Mayrink Verdun, Claudio ; Stöger, Dominik:
Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence Rate.
In: Advances in Neural Information Processing Systems 34 (NeurIPS 2021). - 2021
(Begutachteter Beitrag / peer-reviewed paper)

Balaji, Yogesh ; Sajedi, Mohammadmahdi ; Kalibhat, Neha Mukund ; Ding, Mucong ; Stöger, Dominik ; Soltanolkotabi, Mahdi ; Feizi, Soheil:
Understanding Overparameterization in Generative Adversarial Networks.
In: International Conference on Learning Representations 2021. - Vienna, Austria, 2021
(Begutachteter Beitrag / peer-reviewed paper)

Krahmer, Felix ; Stöger, Dominik:
Complex phase retrieval from subgaussian measurements.
In: The journal of Fourier analysis and applications. 26 (20. November 2020) 6: 89. - 27 S.
ISSN 1069-5869 ; 1531-5851
10.1007/s00041-020-09797-9
(Peer-Review-Journal)

Cagnetti, Filippo ; Perugini, Matteo ; Stöger, Dominik:
Rigidity for perimeter inequality under spherical symmetrisation.
In: Calculus of variations and partial differential equations. 59 (4. August 2020): 139.
ISSN 0944-2669 ; 1432-0835
10.1007/s00526-020-01786-6
(Peer-Review-Journal)

Krahmer, Felix ; Stöger, Dominik:
On the convex geometry of blind deconvolution and matrix completion.
In: Communications on pure and applied mathematics. 74 (2020) 4. - S. 790-832.
ISSN 0010-3640 ; 1097-0312
10.1002/cpa.21957
(Peer-Review-Journal)

Geppert, Jakob ; Krahmer, Felix ; Stöger, Dominik:
Sparse power factorization : balancing peakiness and sample complexity.
In: Advances in computational mathematics. 45 (1. Juni 2019). - S. 1711-1728.
ISSN 1019-7168 ; 1572-9044
10.1007/s10444-019-09698-6
(Peer-Review-Journal)

Jung, Peter ; Krahmer, Felix ; Stöger, Dominik:
Blind demixing and deconvolution at near-optimal rate.
In: IEEE transactions on information theory. 64 (2018) 2. - S. 704-727.
ISSN 0018-9448 ; 1557-9654
10.1109/TIT.2017.2784481
(Peer-Review-Journal)

Stöger, Dominik ; Geppert, Jakob ; Krahmer, Felix:
Sparse power factorization with refined peakiness conditions.
In: 2018 IEEE Statistical Signal Processing Workshop (SSP). - Freiburg im Breisgau, 2018
ISBN 978-1-5386-1571-3
10.1109/SSP.2018.8450850
(Begutachteter Beitrag / peer-reviewed paper)

Geppert, Jakob ; Krahmer, Felix ; Stöger, Dominik:
Refined performance guarantees for Sparse Power Factorization.
In: 2017 International Conference on Sampling Theory and Applications (SampTA). - Tallinn, Estonia, 2017. - S. 509-513
ISBN 978-1-5386-1565-2
10.1109/SAMPTA.2017.8024391
(Begutachteter Beitrag / peer-reviewed paper)

Stöger, Dominik ; Jung, Peter ; Krahmer, Felix:
Blind deconvolution and compressed sensing.
In: 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa). - Aachen, 2016. - S. 24-27
ISBN 978-1-5090-2920-4
(Begutachteter Beitrag / peer-reviewed paper)