Kernel methods in system identification, machine learning and function estimation: A survey G Pillonetto, F Dinuzzo, T Chen, G De Nicolao, L Ljung Automatica 50 (3), 657-682, 2014 | 880 | 2014 |
Learning from distributions via Support Measure Machines K Muandet, B Schölkopf, K Fukumizu, F Dinuzzo Advances in Neural Information Processing Systems 25, 2012 | 230 | 2012 |
Stance classification of context-dependent claims R Bar-Haim, I Bhattacharya, F Dinuzzo, A Saha, N Slonim Proceedings of the 15th Conference of the European Chapter of the …, 2017 | 205 | 2017 |
Higher order sliding mode controllers with optimal reaching F Dinuzzo, A Ferrara IEEE Transactions on Automatic Control 54 (9), 2126-2136, 2009 | 182 | 2009 |
Electricity Demand Forecasting by Multi-Task Learning JB Fiot, F Dinuzzo IEEE Transactions on Smart Grid 9 (2), 544-551, 2018 | 128 | 2018 |
Learning output kernels with block coordinate descent F Dinuzzo, CS Ong, P Gehler, G Pillonetto Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011 | 105 | 2011 |
The representer theorem for Hilbert spaces: a necessary and sufficient condition F Dinuzzo, B Schölkopf Advances in Neural Information Processing Systems 25, 189--196, 2012 | 102 | 2012 |
Kernels for linear time invariant system identification F Dinuzzo SIAM Journal on Control and Optimization 53 (5), 3299–3317, 2015 | 90 | 2015 |
Bayesian online multitask learning of Gaussian processes G Pillonetto, F Dinuzzo, G De Nicolao Pattern Analysis and Machine Intelligence, IEEE Transactions on 32 (2), 193-205, 2010 | 78 | 2010 |
Client–server multitask learning from distributed datasets F Dinuzzo, G Pillonetto, G De Nicolao Neural Networks, IEEE Transactions on 22 (2), 290-303, 2011 | 46 | 2011 |
On the representer theorem and equivalent degrees of freedom of SVR. F Dinuzzo, M Neve, G De Nicolao, UP Gianazza Journal of Machine Learning Research 8 (10), 2007 | 35 | 2007 |
Learning output kernels for multi-task problems F Dinuzzo Neurocomputing 118, 119-126, 2013 | 32 | 2013 |
A Unifying View of Representer Theorems A Argyriou, F Dinuzzo ICML, 2014 | 31 | 2014 |
Learning low-rank output kernels F Dinuzzo, K Fukumizu Asian Conference on Machine Learning, 181-196, 2011 | 22 | 2011 |
Sliding mode optimal regulator for a Bolza-Meyer criterion with non-quadratic state energy terms M Basin, D Calderon-Alvarez, A Ferrara, F Dinuzzo 2009 American Control Conference, 4951-4955, 2009 | 20 | 2009 |
Kernel machines with two layers and multiple kernel learning F Dinuzzo arXiv preprint arXiv:1001.2709, 2010 | 16 | 2010 |
Finite-time output stabilization with second order sliding modes F Dinuzzo, A Ferrara Automatica 45 (9), 2169-2171, 2009 | 13 | 2009 |
Claim polarity identification E Aharoni, R Bar-Haim, I Bhattacharya, F Dinuzzo, D Gutfreund, A Saha, ... US Patent 9,632,998, 2017 | 11 | 2017 |
An algebraic characterization of the optimum of regularized kernel methods F Dinuzzo, G De Nicolao Machine learning 74, 315-345, 2009 | 11 | 2009 |
A second order sliding mode controller with polygonal constraints F Dinuzzo Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held …, 2009 | 9 | 2009 |