Submitted:

Regularized Nyström subsampling in regression and ranking problems under general smoothness assumptions
G.L. Myleiko, S. Pereverzyev Jr., S.G. Solodky
Submitted, 2017 [pdf ]
On the configuration space of planar Closed kinematic Chains
Gerhard Zangerl
Submitted, 2017 [pdf ]
Operator learning approach for the limited view problem in photoacoustic tomography
Florian Dreier, Sergiy Pereverzyev Jr., Markus Haltmeier
Submitted, 2017 [pdf ] [arxiv.org]
Iterative Methods for Photoacoustic Tomography in Attenuating Acoustic Media
Markus Haltmeier, Richard Kowar, Linh V. Nguyen
Submitted, 2017 [pdf ] [arxiv.org]
Total Variation Minimization Compressed Sensing
Felix Krahmer, Christian Kruschel, Michael Sandbichler
Submitted, 2017 [pdf ] [arxiv.org]
Sequential Learning of Analysis Operators
Michael Sandbichler, Karin Schnass
Submitted, 2017 [pdf ] [arxiv.org]
Dictionary Learning from Incomplete Data
Valeriya Naumova, Karin Schnass
Submitted, 2017 [pdf ] [arxiv.org]
Deep Learning for Photoacoustic Tomography from Sparse Data
Stephan Antholzer, Markus Haltmeier, Johannes Schwab
Submitted, 2017 [pdf ] [arxiv.org]

Efficient regularization with wavelet sparsity constraints in PAT
Jürgen Frikel, Markus Haltmeier
Submittet, 2017 [pdf ] [arxiv.org]
Analysis of the Linearized Problem of Quantitative Photoacoustic Tomography
Markus Haltmeier, Lukas Neumann, Linh V. Nguyen, Simon Rabanser
Submitted, 2017 [pdf ] [arxiv.org]
Galaxy And Mass Assembly: Automatic Morphological Classification of Galaxies Using Statistical Learning
S. Sreejith, S. Pereverzyev Jr., L.S. Kelvin, F. Marleau, M. Haltmeier, J. Ebner, et al.
Submitted, 2017
A Galerkin least squares approach for photoacoustic tomography
Johannes Schwab, Sergiy Pereverzyev Jr., Markus Haltmeier
Submitted, 2017 [pdf ] [arxiv.org]
A Machine Learning Framework for Customer Purchase Prediction in the Non-Contractual Setting
Andrés Martínez, Claudia Schmuck, Sergiy Pereverzyev Jr., Clemens Pirker, Markus Haltmeier,
Submitted, 2016 [pdf ]

Convergence radius and sample complexity of ITKM algorithms for dictionary learning
Karin Schnass
Submitted, 2016 [pdf ]