| Accelerated and inexact forward-backward algorithms S Villa, S Salzo, L Baldassarre, A Verri SIAM Journal on Optimization 23 (3), 1607-1633, 2013 | 137 | 2013 |
| Conditional mean embeddings as regressors-supplementary S Grünewälder, G Lever, L Baldassarre, S Patterson, A Gretton, M Pontil arXiv preprint arXiv:1205.4656, 2012 | 89 | 2012 |
| Modelling transition dynamics in MDPs with RKHS embeddings S Grunewalder, G Lever, L Baldassarre, M Pontil, A Gretton arXiv preprint arXiv:1206.4655, 2012 | 83 | 2012 |
| Structured sparsity models for brain decoding from fMRI data L Baldassarre, J Mourao-Miranda, M Pontil 2012 Second International Workshop on Pattern Recognition in NeuroImaging, 5-8, 2012 | 73 | 2012 |
| Learning-based compressive subsampling L Baldassarre, YH Li, J Scarlett, B Gözcü, I Bogunovic, V Cevher IEEE Journal of Selected Topics in Signal Processing 10 (4), 809-822, 2016 | 47 | 2016 |
| Convexity in source separation: Models, geometry, and algorithms MB McCoy, V Cevher, QT Dinh, A Asaei, L Baldassarre IEEE Signal Processing Magazine 31 (3), 87-95, 2014 | 46 | 2014 |
| Multi-output learning via spectral filtering L Baldassarre, L Rosasco, A Barla, A Verri Machine learning 87 (3), 259-301, 2012 | 46 | 2012 |
| Group-sparse model selection: Hardness and relaxations L Baldassarre, N Bhan, V Cevher, A Kyrillidis, S Satpathi IEEE Transactions on Information Theory 62 (11), 6508-6534, 2016 | 33 | 2016 |
| Localizing and comparing weight maps generated from linear kernel machine learning models J Schrouff, J Cremers, G Garraux, L Baldassarre, J Mourão-Miranda, ... 2013 International Workshop on Pattern Recognition in Neuroimaging, 124-127, 2013 | 29 | 2013 |
| Vector field learning via spectral filtering L Baldassarre, L Rosasco, A Barla, A Verri Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010 | 26 | 2010 |
| Sparsity is better with stability: Combining accuracy and stability for model selection in brain decoding L Baldassarre, M Pontil, J Mourão-Miranda Frontiers in neuroscience 11, 62, 2017 | 24 | 2017 |
| Model-based sketching and recovery with expanders B Bah, L Baldassarre, V Cevher Proceedings of the twenty-fifth annual ACM-SIAM symposium on Discrete …, 2014 | 20 | 2014 |
| Structured sparsity: Discrete and convex approaches A Kyrillidis, L Baldassarre, M El Halabi, Q Tran-Dinh, V Cevher Compressed Sensing and its Applications, 341-387, 2015 | 16 | 2015 |
| A general framework for structured sparsity via proximal optimization L Baldassarre, J Morales, A Argyriou, M Pontil Artificial Intelligence and Statistics, 82-90, 2012 | 16 | 2012 |
| Optimal computational trade-off of inexact proximal methods P Machart, S Anthoine, L Baldassarre arXiv preprint arXiv:1210.5034, 2012 | 15 | 2012 |
| Towards a theoretical framework for learning multi-modal patterns for embodied agents N Noceti, B Caputo, C Castellini, L Baldassarre, A Barla, L Rosasco, ... International Conference on Image Analysis and Processing, 239-248, 2009 | 12 | 2009 |
| Structured sampling and recovery of ieeg signals L Baldassarre, C Aprile, M Shoaran, Y Leblebici, V Cevher 2015 IEEE 6th International Workshop on Computational Advances in Multi …, 2015 | 10 | 2015 |
| Tractability of interpretability via selection of group-sparse models N Bhan, L Baldassarre, V Cevher 2013 IEEE International Symposium on Information Theory, 1037-1041, 2013 | 9 | 2013 |
| Vector valued regression for iron overload estimation L Baldassarre, A Barla, B Gianesin, M Marinelli 2008 19th International Conference on Pattern Recognition, 1-4, 2008 | 9 | 2008 |
| Learning-based near-optimal area-power trade-offs in hardware design for neural signal acquisition C Aprile, L Baldassarre, V Gupta, J Yoo, M Shoaran, Y Leblebici, ... 2016 International Great Lakes Symposium on VLSI (GLSVLSI), 433-438, 2016 | 8 | 2016 |
Volkan CevherAssociate Professor, Laboratory for Information and Inference Systems, EPFLVerified email at epfl.ch
