| Compressed sensing and redundant dictionaries H Rauhut, K Schnass, P Vandergheynst IEEE Transactions on Information Theory 54 (5), 2210-2219, 2008 | 720 | 2008 |
| Atoms of all channels, unite! Average case analysis of multi-channel sparse recovery using greedy algorithms R Gribonval, H Rauhut, K Schnass, P Vandergheynst Journal of Fourier analysis and Applications 14 (5), 655-687, 2008 | 224 | 2008 |
| Dictionary identification - sparse matrix-factorization via l1 minimization R Gribonval, K Schnass Information Theory, IEEE Transactions on 56 (7), 3523-3539, 2010 | 209 | 2010 |
| Dictionary preconditioning for greedy algorithms K Schnass, P Vandergheynst IEEE Transactions on Signal Processing 56 (5), 1994-2002, 2008 | 177 | 2008 |
| Learning functions of few arbitrary linear parameters in high dimensions M Fornasier, K Schnass, J Vybiral Foundations of Computational Mathematics 12, 229-262, 2012 | 112 | 2012 |
| On the identifiability of overcomplete dictionaries via the minimisation principle underlying K-SVD K Schnass Applied and Computational Harmonic Analysis, 2014, 2014 | 80 | 2014 |
| Average performance analysis for thresholding K Schnass, P Vandergheynst IEEE Signal Processing Letters 14 (11), 828-831, 2007 | 79 | 2007 |
| Convergence radius and sample complexity of ITKM algorithms for dictionary learning K Schnass Applied and Computational Harmonic Analysis 45 (1), 22-58, 2018 | 51 | 2018 |
| Local identification of overcomplete dictionaries K Schnass Journal of Machine Learning Research, 2015 | 51 | 2015 |
| Average performance of orthogonal matching pursuit (OMP) for sparse approximation K Schnass IEEE Signal Processing Letters 25 (12), 1865-1869, 2018 | 32 | 2018 |
| Average case analysis of multichannel thresholding R Gribonval, B Mailhe, H Rauhut, K Schnass, P Vandergheynst 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 27 | 2007 |
| Some recovery conditions for basis learning by L1-minimization R Gribonval, K Schnass 2008 3rd International Symposium on Communications, Control and Signal …, 2008 | 22 | 2008 |
| Dictionary identifiability from few training samples R Gribonval, K Schnass 2008 16th European Signal Processing Conference, 1-5, 2008 | 19 | 2008 |
| Dictionary learning—from local towards global and adaptive MC Pali, K Schnass Information and Inference: A Journal of the IMA 12 (3), 1295-1346, 2023 | 17 | 2023 |
| Dictionary learning from incomplete data for efficient image restoration V Naumova, K Schnass 2017 25th European signal processing conference (EUSIPCO), 1425-1429, 2017 | 15 | 2017 |
| Compressed learning of high-dimensional sparse functions K Schnass, J Vybíral 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 15 | 2011 |
| A Personal Introduction to Theoretical Dictionary Learning K Schnass Internationale Mathematische Nachrichten, 2015 | 13 | 2015 |
| Fast dictionary learning from incomplete data V Naumova, K Schnass EURASIP journal on advances in signal processing 2018, 1-21, 2018 | 12 | 2018 |
| Average performance of OMP and Thresholding under dictionary mismatch MC Pali, S Ruetz, K Schnass IEEE Signal Processing Letters 29, 1077-1081, 2022 | 8 | 2022 |
| Gabor Multipliers: A Self-contained Survey K Schnass master’s thesis, Univ. of Vienna, 2004 | 8 | 2004 |
Pierre VandergheynstProfessor of Electrical Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL)在 epfl.ch 的电子邮件经过验证
