A. Tzioufas, Monotonicity of escape probabilities for branching random walks on Zd, arXiv:1911.09563, 2019. [pdf]

K. Schnass, Dictionary learning - from local towards global and adaptive, arXiv:1804.07101, 2018. [pdf] [toolbox]


K. Schnass and F. Teixeira, Compressed dictionary learning, Journal of Fourier Analysis and Applications, accepted, 2020. [pdf] [probox] [toybox]

S. Antholzer, C. Wolf, M. Sandbichler, M. Dielacher and M. Haltmeier, Compressive time-of-flight 3D imaging using block-structured sensing matrices, Inverse Problems, 35(4), 2019. [pdf]

M. Sandbichler and K. Schnass, Online and stable learning of analysis operators, IEEE Transactions on Signal Processing, 67(1):41--53, 2019. [pdf] [toolbox]

K. Schnass, Average performance of Orthogonal Matching Pursuit (OMP) for sparse approximation, IEEE Signal Processing Letters (arXiv:1809.06684), 25(12):1865--1869, 2018. [pdf]

V. Naumova and K. Schnass, Fast dictionary learning from incomplete data, EURASIP Journal on Advances in Signal Processing, 2018. [pdf] [toolbox]

M. Haltmeier, M. Sandbichler, T. Berer, J. Bauer-Marschallinger, P. Burgholzer and L. Nguyen, A sparsification and reconstruction strategy for compressed sensing photoacoustic tomography, The Journal of the Acoustical Society of America, 143(6), 2018. [pdf]

K. Schnass, Convergence radius and sample complexity of ITKM algorithms for dictionary learning, Applied and Computational Harmonic Analysis, 45(1):22–58, 2018. [pdf] [toolbox]


V. Naumova and K. Schnass, Dictionary learning from incomplete data for efficient image restoration, EUSIPCO17. [pdf] [toolbox]

S. Antholzer, C. Wolf, M. Sandbichler, M. Dielacher and M. Haltmeier, Compressive time- of-flight imaging, SampTA17, Tallinn, EE, 2017. [link]

Book Chapter

F. Krahmer, C. Kruschel and M. Sandbichler, Total variation minimization in compressed sensing, 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]


M. Tiefenthaler, Integrating low-rank components into weighted K-SVD for dictionary based inpainting, BSc thesis, University of Innsbruck, 2018. [pdf]

M. Sandbichler, Compressed sensing, sparsity and related topics, PhD thesis, University of Innsbruck, 2018. [pdf]

E. Höck, Hard Thresholding Pursuit for Sparse Approximation, BSc thesis, University of Innsbruck, 2016. [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.


Nach oben scrollen