Publications

Preprints

Convergence of alternating minimisation algorithms for dictionary learning
S. Ruetz and K. Schnass
arXiv:2304.01768, 2023. [pdf]
Non-asymptotic bounds for inclusion probabilities in rejective sampling
S. Ruetz and K. Schnass
arXiv:2212.09391, 2022. [pdf]
Adapted variable density subsampling for compressed sensing
S. Ruetz
arXiv:2206.13796, 2022. [pdf]

Journal

Dictionary learning - from local towards global and adaptive
M.C. Pali and K. Schnass
Information and Inference: A Journal of the IMA, 12(3):1295-1346, 2023. [v1pdf] [v2pdf] [toolbox]
Deep supervised dictionary learning by algorithmic unrolling - application to fast 2D dynamic MR image reconstruction
A. Kofler, M.C. Pali, T. Schaeffter and C. Kolbitsch
Medical Physics, 50(5):2939-2960, 2023. [link]
Average performance of OMP and Thresholding under dictionary mismatch
M.C. Pali, S. Ruetz and K. Schnass
IEEE Signal Processing Letters, 29:1077-1081, 2022. [pdf]
Submatrices with non-uniformly selected random supports and insights into sparse approximation
S. Ruetz and K. Schnass
SIAM Journal on Matrix Analysis and Applications (SIMAX), 42(3):1268-1289, 2021. [pdf]
Adaptive sparsity level and dictionary size estimation for image reconstruction in accelerated 2D radial cine MRI
M.C. Pali, T. Schaeffter, C. Kolbitsch and A. Kofler
Medical Physics, 48(1):178-192, 2021. [pdf] [editor's choice] [toolbox]
Compressed dictionary learning
K. Schnass and F. Teixeira
Journal of Fourier Analysis and Applications 26, Art. Nr. 33, 2020. [pdf] [probox] [toybox]
Monotonicity of escape probabilities for branching random walks on Z^d
A. Tzioufas
Statistics and Probability Letters 167, 2020. [pdf]
Compressive time-of-flight 3D imaging using block-structured sensing matrices
S. Antholzer, C. Wolf, M. Sandbichler, M. Dielacher and M. Haltmeier
Inverse Problems, 35(4), 2019. [pdf]
Online and stable learning of analysis operators
M. Sandbichler and K. Schnass
IEEE Transactions on Signal Processing, 67(1):41--53, 2019. [pdf] [toolbox]
Average performance of Orthogonal Matching Pursuit (OMP) for sparse approximation
K. Schnass
IEEE Signal Processing Letters (arXiv:1809.06684), 25(12):1865--1869, 2018. [pdf]
Fast dictionary learning from incomplete data
V. Naumova and K. Schnass
EURASIP Journal on Advances in Signal Processing, 2018. [pdf] [toolbox]
A sparsification and reconstruction strategy for compressed sensing photoacoustic tomography
M. Haltmeier, M. Sandbichler, T. Berer, J. Bauer-Marschallinger, P. Burgholzer and L. Nguyen
The Journal of the Acoustical Society of America, 143(6), 2018. [pdf]
Convergence radius and sample complexity of ITKM algorithms for dictionary learning
K. Schnass
Applied and Computational Harmonic Analysis, 45(1):22–58, 2018. [pdf] [toolbox]

Conference

A good reason for using OMP: average case results
K. Schnass
SPARS19. [extended abstract]
The adaptive dictionary learning toolbox
C. Rusu and K. Schnass
SPARS19. [extended abstract]
Relaxed contractivity conditions for dictionary learning via Iterative Thresholding and K residual Means
M.C. Pali, K. Schnass and A. Steinicke
SPARS19. [extended abstract]
Sequential learning of analysis operators
M. Sandbichler and K. Schnass
SPARS17. [extended abstract]
Compressed dictionary learning
F. Teixeira and K. Schnass
SPARS17. [extended abstract]
Dictionary learning from incomplete data for efficient image restoration
V. Naumova and K. Schnass
EUSIPCO17. [pdf] [toolbox]
Compressive time-of-flight imaging
S. Antholzer, C. Wolf, M. Sandbichler, M. Dielacher and M. Haltmeier
SampTA17. [link]

Book Chapter

Total variation minimization in compressed sensing
F. Krahmer, C. Kruschel and M. Sandbichler
In: Boche H., Caire G., Calderbank R., März M., Kutyniok G., Mathar R. (eds) Compressed Sensing and its Applications, Applied and Numerical Harmonic Analysis, pppp 333-358, Birkhäuser, Cham, 2017. [pdf]

PhD-theses

Compressed sensing and dictionary learning with non-uniform support distribution
S. Ruetz
PhD thesis, University of Innsbruck, 2022. [pdf]
Dictionary learning & sparse modelling
M.C. Pali
PhD thesis, University of Innsbruck, 2021. [pdf]
Compressed sensing, sparsity and related topics
M. Sandbichler
PhD thesis, University of Innsbruck, 2018. [pdf]

Copyright Blabla

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.