| Alternating least-squares for low-rank matrix reconstruction D Zachariah, M Sundin, M Jansson, S Chatterjee IEEE Signal Processing Letters 19 (4), 231-234, 2012 | 79 | 2012 |
| A connectedness constraint for learning sparse graphs M Sundin, A Venkitaraman, M Jansson, S Chatterjee 2017 25th European Signal Processing Conference (EUSIPCO), 151-155, 2017 | 18 | 2017 |
| Alternating strategies with internal ADMM for low-rank matrix reconstruction K Li, M Sundin, CR Rojas, S Chatterjee, M Jansson Signal Processing 121, 153-159, 2016 | 17 | 2016 |
| Combined modeling of sparse and dense noise improves Bayesian RVM M Sundin, S Chatterjee, M Jansson 2014 22nd European Signal Processing Conference (EUSIPCO), 1841-1845, 2014 | 8 | 2014 |
| Relevance singular vector machine for low-rank matrix reconstruction M Sundin, CR Rojas, M Jansson, S Chatterjee IEEE Transactions on Signal Processing 64 (20), 5327-5339, 2016 | 7 | 2016 |
| Bayesian learning for time-varying linear prediction of speech A Casamitjana, M Sundin, P Ghosh, S Chatterjee 2015 23rd European Signal Processing Conference (EUSIPCO), 325-329, 2015 | 6 | 2015 |
| Relevance singular vector machine for low-rank matrix sensing M Sundin, S Chatterjee, M Jansson, CR Rojas Signal Processing and Communications (SPCOM), 2014 International Conference …, 2014 | 6 | 2014 |
| Bayesian learning for robust principal component analysis M Sundin, S Chatterjee, M Jansson 2015 23rd European Signal Processing Conference (EUSIPCO), 2361-2365, 2015 | 5 | 2015 |
| Beamformers for sparse recovery M Sundin, D Sundman, M Jansson 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 5 | 2013 |
| Conditional prior based LMMSE estimation of sparse signals M Sundin, M Jansson, S Chatterjee 21st European Signal Processing Conference (EUSIPCO 2013), 1-5, 2013 | 3 | 2013 |
| A dynamical symmetry for supermembranes J de Woul, J Hoppe, D Lundholm, M Sundin arXiv preprint arXiv:1004.0266, 2010 | 3 | 2010 |
| Combined modeling of sparse and dense noise for improvement of relevance vector machine M Sundin, S Chatterjee, M Jansson arXiv preprint arXiv:1501.02579, 2015 | 2 | 2015 |
| Bayesian Cramer-Rao bounds for factorized model based low rank matrix reconstruction M Sundin, S Chatterjee, M Jansson 2016 24th European Signal Processing Conference (EUSIPCO), 1227-1231, 2016 | 1 | 2016 |
| Bayesian methods for sparse and low-rank matrix problems M Sundin KTH Royal Institute of Technology, 2016 | 1 | 2016 |
| Greedy minimization of l1-norm with high empirical success M Sundin, S Chatterjee, M Jansson 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 1 | 2015 |
| Bayesian learning for low-rank matrix reconstruction M Sundin, CR Rojas, M Jansson, S Chatterjee arXiv preprint arXiv:1501.05740, 2015 | 1 | 2015 |
| Alternating Strategies Are Good For Low-Rank Matrix Reconstruction K Li, M Sundin, CR Rojas, S Chatterjee, M Jansson arXiv preprint arXiv:1407.3410, 2014 | 1 | 2014 |
| Knockout studies of Panc1 cells M Sundin | | 2021 |
| Extrinsic curvature effects in brane-world scenarios E Langmann, M Sundin arXiv preprint arXiv:1103.3230, 2011 | | 2011 |
| A dynamical symmetry for supermembranes J Hoppe, D Lundholm, M Sundin Journal of High Energy Physics 2011 (3), 2011 | | 2011 |
Magnus JanssonKTH Royal Institute of Technology, School of Electrical engineering and computer science, Division在 kth.se 的电子邮件经过验证
