Veröffentlichungen "Maly, Johannes"

2022

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  Caragea, Andrei ; Lee, Dae Gwan ; Maly, Johannes ; Pfander, Götz E. ; Voigtlaender, Felix:
  Quantitative approximation results for complex-valued neural networks.
  In: SIAM Journal on Mathematics of Data Science. 4 (2022) 2. - S. 553-580.
  ISSN 2577-0187
  0.1137/21M1429540
  (Peer-Review-Journal)

2021

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  Kereta, Željko ; Maly, Johannes ; Naumova, Valeriya:
  Computational approaches to non-convex, sparsity-inducing multi-penalty regularization.
  In: Inverse Problems. 37 (20. April 2021) 5: 055008. - 22 S.
  ISSN 0266-5611 ; 1361-6420
  10.1088/1361-6420/abdd46
  (Peer-Review-Journal)
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  Iwen, Mark A. ; Krahmer, Felix ; Krause-Solberg, Sara ; Maly, Johannes:
  On Recovery Guarantees for One-Bit Compressed Sensing on Manifolds.
  In: Discrete & computational geometry. 65 (15. April 2021). - S. 953-998.
  ISSN 0179-5376 ; 1432-0444
  10.1007/s00454-020-00267-z
  (Peer-Review-Journal)
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  Fornasier, Massimo ; Maly, Johannes ; Naumova, Valeriya:
  Robust Recovery of Low-Rank Matrices with Non-Orthogonal Sparse Decomposition from Incomplete Measurements.
  In: Applied mathematics and computation. 392 (1. März 2021).
  ISSN 0096-3003
  10.1016/j.amc.2020.125702
  (Peer-Review-Journal)
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  Dirksen, Sjoerd ; Maly, Johannes ; Rauhut, Holger:
  Covariance estimation under one-bit quantization.
  Eichstätt : arXiv, 2021. - 26 S.
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  Maly, Johannes ; Yang, Tainyu ; Dirksen, Sjoerd ; Rauhut, Holger ; Caire, Giuseppe:
  New challenges in covariance estimation : multiple structures and coarse quantization.
  Eichstätt : arXiv, 2021. - 26 S.
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  Caragea, Andrei ; Lee, Dae Gwan ; Maly, Johannes ; Pfander, Götz E.:
  Quantitative approximation results for complex-valued neural networks.
  Eichstätt : arXiv, 2021. - 19 S.
  arxiv:2102.13092
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  Maly, Johannes:
  Robust Sensing of Low-Rank Matrices with Non-Orthogonal Sparse Decomposition.
  Eichstätt : arXiv, 2021. - 23 S.
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  Boßmann, Florian ; Krause-Solberg, Sara ; Maly, Johannes ; Sissouno, Nada:
  Structural Sparsity in Multiple Measurements.
  Eichstätt : arXiv, 2021. - 12 S.
  10.48550/arXiv.2103.01908
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  Jung, Hans Christian ; Maly, Johannes ; Palzer, Lars ; Stollenwerk, Alexander:
  Quantized Compressed Sensing by Rectified Linear Units.
  In: IEEE transactions on information theory. 67 (2021) 6. - S. 4125-4149.
  ISSN 0018-9448 ; 1557-9654
  10.1109/TIT.2021.3070789
  (Peer-Review-Journal)
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  Jung, Hans Christian ; Maly, Johannes ; Palzer, Lars ; Stollenwerk, Alexander:
  Quantized Compressed Sensing by Rectified Linear Units.
  In: Proceedings in applied mathematics and mechanics : PAMM. (2021).
  ISSN 1617-7061
  10.1002/pamm.202000015
  (Peer-Review-Journal)

2020

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  Chou, Hung-Hsu ; Gieshoff, Carsten ; Maly, Johannes ; Rauhut, Holger:
  Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank.
  Eichstätt : arXiv, 2020. - 38 S.
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  Maly, Johannes ; Palzer, Lars:
  Analysis of hard-thresholding for distributed compressed sensing with one-bit measurements.
  In: Information and Inference : a Journal of the IMA. 9 (2020) 2. - S. 455-471.
  ISSN 2049-8772 ; 2049-8764
  10.1093/imaiai/iaz004
  (Peer-Review-Journal)
• Guth, Adrien ; Culotta-Lopéz, Cosme ; Maly, Johannes ; Rauhut, Holger ; Heberling, Dirk:
  Polyhedral Sampling Structures for Phaseless Spherical Near-Field Antenna Measurements.
  In: Proceedings of 2020 Antenna Measurement Techniques Association Symposium (AMTA). - Newport, RI, USA : IEEE, 2020
  ISBN 978-1-7362351-0-2 ; 978-1-7281-9868-2
  (Begutachteter Beitrag / peer-reviewed paper)

2019

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  Dirksen, Sjoerd ; Iwen, Mark A. ; Krause-Solberg, Sara ; Maly, Johannes:
  Robust One-bit Compressed Sensing With Manifold Data.
  In: Proceedings of 2019 13th International conference on Sampling Theory and Applications (SampTA). - Bordeaux : IEEE, 2019
  ISBN 978-1-7281-3741-4 ; 978-1-7281-3740-7
  10.1109/SampTA45681.2019.9030809
  (Begutachteter Beitrag / peer-reviewed paper)

2017

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  Krause-Solberg, Sara ; Maly, Johannes:
  A tractable approach for one-bit Compressed Sensing on manifolds.
  In: Proceedings of 2017 International Conference on Sampling Theory and Applications (SampTA), Tallinn, Estonia. - Tallinn, Estonia : IEEE, 2017
  ISBN 978-1-5386-1565-2 ; 978-1-5386-1564-5
  10.1109/SAMPTA.2017.8024465
  (Begutachteter Beitrag / peer-reviewed paper)