| Accelerated and inexact forward-backward algorithms S Villa, S Salzo, L Baldassarre, A Verri SIAM Journal on Optimization 23 (3), 1607-1633, 2013 | 189 | 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 | 145 | 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 | 119 | 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 | 84 | 2016 |
| 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 | 82 | 2012 |
| Multi-output learning via spectral filtering L Baldassarre, L Rosasco, A Barla, A Verri Machine learning 87, 259-301, 2012 | 66 | 2012 |
| 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 | 55 | 2014 |
| 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 | 41 | 2013 |
| 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 | 38 | 2016 |
| 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 | 35 | 2017 |
| Vector field learning via spectral filtering L Baldassarre, L Rosasco, A Barla, A Verri Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010 | 30 | 2010 |
| Structured sparsity: Discrete and convex approaches A Kyrillidis, L Baldassarre, ME Halabi, Q Tran-Dinh, V Cevher Compressed Sensing and its Applications: MATHEON Workshop 2013, 341-387, 2015 | 21 | 2015 |
| 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 | 21 | 2014 |
| Optimal computational trade-off of inexact proximal methods P Machart, S Anthoine, L Baldassarre arXiv preprint arXiv:1210.5034, 2012 | 20 | 2012 |
| A general framework for structured sparsity via proximal optimization L Baldassarre, J Morales, A Argyriou, M Pontil Artificial Intelligence and Statistics, 82-90, 2012 | 17 | 2012 |
| Adaptive learning-based compressive sampling for low-power wireless implants C Aprile, K Ture, L Baldassarre, M Shoaran, G Yilmaz, F Maloberti, ... IEEE Transactions on Circuits and Systems I: Regular Papers 65 (11), 3929-3941, 2018 | 16 | 2018 |
| 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 | 11 | 2015 |
| On sparsity inducing regularization methods for machine learning A Argyriou, L Baldassarre, CA Micchelli, M Pontil Empirical Inference: Festschrift in Honor of Vladimir N. Vapnik, 205-216, 2013 | 10 | 2013 |
| Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents. N Noceti, B Caputo, C Castellini, L Baldassarre, A Barla, L Rosasco, ... ICIAP 9, 239-248, 2009 | 10 | 2009 |
| 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, ... Proceedings of the 26th edition on Great Lakes Symposium on VLSI, 433-438, 2016 | 9 | 2016 |
Volkan CevherAssociate Professor, LIONS, EPFL. Amazon Scholar.Verified email at epfl.ch
