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Teaching |
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Code |
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Welcome to my page! I am an assistant professor working on mathematics of data science and machine learning. My former research has been focused on compressed sensing and the influence of quantization on signal reconstruction. I am currently interested in
I am a relAI Fellow and an MCML Associate. |
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Contact
Current address: Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence, LMU Munich, Akademiestr. 7, D-80799 München
E-mail: maly(at)math(dot)lmu(dot)de
Short CV
- 10/2022 - now: Assistant professor for “Mathematical Data Science” at the chair of Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence at LMU, Munich
- 11/2020 - 09/2022: PostDoc (akademischer Rat auf Zeit) at the Department of Scientific Computing at Catholic University of Eichstaett-Ingolstadt
- 02/2019 - 10/2020: PostDoc at the Chair for Mathematics of Data Processing at RWTH Aachen University
- 01/2016 - 01/2019: PhD at the Chair for Applied and Numerical Analysis and Optimization and Data Analysis at TUM, Munich, under supervision of Prof. Massimo Fornasier
- 10/2013 - 09/2015: M.Sc. in mathematics at TUM, Munich
- 05/2011 - 09/2013: B.Sc. in mathematics at TUM, Munich
Teaching
LMU
- 04/2025 - 09/2025: “Mathematische Einführung in Data Science” (Lecture)
- 04/2024 - 09/2024: “Convex Optimization” (Lecture)
- 10/2023 - 03/2024: “High-dimensional Probability” (Lecture)
- 04/2023 - 09/2023: “Convex Optimization for Data Science” (Lecture)
- 10/2022 - 03/2023: “Mathematical Signal and Image Processing” (Lecture)
Catholic University of Eichstaett/Ingolstadt
- 04/2022 - 09/2022: “Introduction to Scientific Computing” (Lecture+Exercises)
- 10/2021 - 03/2022: “Mathematics for Economics” (Lecture)
- 04/2021 - 09/2021: “Introduction to Scientific Computing” (Lecture+Exercises)
- 11/2020 - 03/2021: “Introduction to Numerical Analysis” (Lecture+Exercises)
RWTH Aachen University
- 04/2020 - 09/2020: Teaching assistant for “Optimization”
- 10/2019 - 03/2020: Teaching assistant for “Repetitorium - Higher Mathematics II”
- 04/2019 - 09/2019: Teaching assistant for “Higher Mathematics II”
Technical University of Munich
- 04/2018 - 09/2018: Teaching assistant for “Foundations of Data Analysis”
Publications
Preprints
- V. Fojtik, M. Matveev, H.–H. Chou, G. Kutyniok, and J. Maly: “Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization”, 2025, arXiv preprint
- S. Dirksen, W. Li, and J. Maly: “Subspace and DOA estimation under coarse quantization”, 2025, arXiv preprint
- H.–H. Chou, J. Maly, and D. Stöger: “How to induce regularization in generalized linear models: A guide to reparametrizing gradient flow”, 2023, arXiv preprint
Journal publications
2024
- S. Dirksen and J. Maly: “Tuning-free one-bit covariance estimation using data-driven dithering”, 2024, IEEE Transactions on Information Theory, (arXiv)
- H.–H. Chou, C. Gieshoff, J. Maly, and H. Rauhut: “Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank”, 2024, Applied and Computational Harmonic Analysis, (arXiv)
- T. Yang, J. Maly, S. Dirksen, and G. Caire: “Plug-in Channel Estimation with Dithered Quantized Signals in Spatially Non-Stationary Massive MIMO Systems”, 2024, IEEE Transactions on Communications, (arXiv)
2023
- J. Maly: “Robust Sensing of Low-Rank Matrices with Non-Orthogonal Sparse Decomposition”, 2023, Applied and Computational Harmonic Analysis, (arXiv)
- J. Maly and R. Saab: “A simple approach for quantizing neural networks”, 2023, Applied and Computational Harmonic Analysis, (arXiv)
- H.–H. Chou, J. Maly, and H. Rauhut: “More is Less: Inducing Sparsity via Overparameterization”, 2023, Information and Inference: A Journal of the IMA, (arXiv)
2022
- S. Dirksen, J. Maly, and H. Rauhut: “Covariance estimation under one-bit quantization”, 2022, Annals of Statistics, (arXiv)
- A. Caragea, D. G. Lee, J. Maly, G. Pfander, and F. Voigtlaender: “Quantitative approximation results for complex-valued neural networks”, 2022, SIAM Journal on Mathematics of Data Science (SIMODS), (arXiv)
2021
- F. Boßmann, S. Krause-Solberg, J. Maly, and N. Sissouno: “Structural Sparsity in Multiple Measurements”, 2021, IEEE Transactions on Signal Processing, (arXiv)
- Z. Kereta, J. Maly, and V. Naumova: “Computational approaches to non-convex, sparsity-inducing multi-penalty regularization”, 2021, Inverse Problems, (arXiv)
- M. Iwen, F. Krahmer, S. Krause-Solberg, and J. Maly: “On Recovery Guarantees for One-Bit Compressed Sensing on Manifolds”, 2021, Discrete and Computational Geometry, (arXiv)
- H. C. Jung, J. Maly, L. Palzer, and A. Stollenwerk: “Quantized Compressed Sensing by Rectified Linear Units”, 2021, IEEE Transactions on Information Theory, (arXiv)
2020
- M. Fornasier, J. Maly and V. Naumova: “Robust Recovery of Low-Rank Matrices with Non-Orthogonal Sparse Decomposition from Incomplete Measurements”, 2020, Applied Mathematics and Computation, (arXiv)
2019
- J. Maly and L. Palzer: “Analysis of Hard-Thresholding for Distributed Compressed Sensing with One-Bit Measurements”, 2019, Information and Inference: A Journal of the IMA, (arXiv)
Conference publications
2025
- H.–H. Chou, J. Maly, C. Mayrink Verdun, B. Freitas Paulo da Costa, and H. Mirandola: “Get rid of your constraints and reparametrize: A study in NNLS and implicit bias”, 2025, to appear in International Conference on Artificial Intelligence and Statistics, (arXiv)
2023
- C. Kümmerle and J. Maly: “Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares”, 2023, NeurIPS 2023, (arXiv)
2021
- S. Dirksen, J. Maly, and H. Rauhut: “Covariance estimation under one-bit quantization”, 2021, Proceedings in Applied Mathematics and Mechanics — PAMM
- H. C. Jung, J. Maly, L. Palzer, and A. Stollenwerk: “Quantized Compressed Sensing by Rectified Linear Units”, 2021, Proceedings in Applied Mathematics and Mechanics — PAMM
2020
- A. Guth, C. Culotta-López, J. Maly, H. Rauhut, and D. Heberling: “Polyhedral Sampling Structures for Phaseless Spherical Near-Field Antenna Measurements”, 2020, 42nd Antenna Measurement Techniques Association Symposium (AMTA)
- H. C. Jung, J. Maly, L. Palzer, and A. Stollenwerk: “Quantized Compressed Sensing by Rectified Linear Units”, 2020, iTWIST’20
2019
- S. Dirksen, M. Iwen, S. Krause-Solberg, and J. Maly: “Robust One-bit Compressed Sensing With Manifold Data”, 2019, International Conference on Sampling Theory and Applications (SampTA)
- H. C. Jung, J. Maly, L. Palzer, and A. Stollenwerk: “One-Bit Compressed Sensing by Convex Relaxation of the Hamming Distance”, 2019, SPARS workshop
- Z. Kereta, J. Maly, and V. Naumova: Linear convergence and support recovery for non-convex multi-penalty regularisation, 2019, SPARS workshop
2017
- M. Fornasier, J. Maly and V. Naumova: “Robust Recovery of Low-Rank Matrices using Multi-Penalty Regularization”, 2017, NIPS workshop Optimization for Machine Learning
- S. Krause-Solberg and J. Maly: “A tractable approach for one-bit Compressed Sensing on manifolds”, 2017, International Conference on Sampling Theory and Applications (SampTA)
Book chapters
- J. Maly, T. Yang, S. Dirksen, H. Rauhut, and G. Caire: “New challenges in covariance estimation: multiple structures and coarse quantization” in Compressed Sensing in Information Processing, 2021, Springer, (arXiv)
Theses
- J. Maly: “Recovery Algorithms for Quantized Compressed Sensing”, 2019, Phd thesis
- J. Maly: “Weighted Energy-Dissipation Approximation for an Optimal Control Problem”, 2015, Master’s thesis
Code
- Supplementary material for “Tuning-free one-bit covariance estimation using data-driven dithering”
- Supplementary material for “Robust Sensing of Low-Rank Matrices with Non-Orthogonal Sparse Decomposition”
- Supplementary material for “Robust Recovery of Low-Rank Matrices with Non-Orthogonal Sparse Decomposition from Incomplete Measurements”
- Supplementary material for “On Recovery Guarantees for One-Bit Compressed Sensing on Manifolds”