Marco Signoretto
Marco Signoretto
ESAT-STADIUS, KU Leuven
Verified email at esat.kuleuven.be
TitleCited byYear
Learning with tensors: a framework based on convex optimization and spectral regularization
M Signoretto, QT Dinh, L De Lathauwer, JAK Suykens
Machine Learning 94 (3), 303-351, 2014
1532014
Tensor versus matrix completion: a comparison with application to spectral data
M Signoretto, R Van de Plas, B De Moor, JAK Suykens
EEE Signal Processing Letters 18 (7), 403-406, 2011
1172011
Nuclear norms for tensors and their use for convex multilinear estimation
M Signoretto, L De Lathauwer, JAK Suykens
1122010
A kernel-based framework to tensorial data analysis
M Signoretto, L De Lathauwer, JAK Suykens
Neural networks 24 (8), 861-874, 2011
762011
Nonlinear acoustic echo cancellation based on a sliding-window leaky kernel affine projection algorithm
JM Gil-Cacho, M Signoretto, T van Waterschoot, M Moonen, SH Jensen
IEEE Transactions on Audio, Speech, and Language Processing 21 (9), 1867-1878, 2013
462013
Incorporating structural information from the multichannel EEG improves patient-specific seizure detection
B Hunyadi, M Signoretto, W Van Paesschen, JAK Suykens, S Van Huffel, ...
Clinical Neurophysiology 123 (12), 2352-2361, 2012
432012
An equivalence between the lasso and support vector machines
M Jaggi
Regularization, optimization, kernels, and support vector machines, 1-26, 2013
292013
An SVD-free approach to a class of structured low rank matrix optimization problems with application to system identification
M Signoretto, V Cevher, JA Suykens
IEEE Conf. on Decision and Control, 2013
222013
Regularization, optimization, kernels, and support vector machines
JAK Suykens, M Signoretto, A Argyriou
CRC Press, 2014
182014
Hybrid conditional gradient-smoothing algorithms with applications to sparse and low rank regularization
A Argyriou, M Signoretto, J Suykens
Regularization, Optimization, Kernels, and Support Vector Machines, 53-82, 2014
162014
Learning tensors in reproducing kernel Hilbert spaces with multilinear spectral penalties
M Signoretto, L De Lathauwer, JAK Suykens
arXiv preprint arXiv:1310.4977, 2013
152013
Classification of multichannel signals with cumulant-based kernels
M Signoretto, E Olivetti, L De Lathauwer, JAK Suykens
IEEE Transactions on Signal Processing 60 (5), 2304-2314, 2012
152012
Quadratically constrained quadratic programming for subspace selection in kernel regression estimation
M Signoretto, K Pelckmans, J Suykens
International Conference on Artificial Neural Networks (ICANN), 175-184, 2008
122008
High level high performance computing for multitask learning of time-varying models
M Signoretto, E Frandi, Z Karevan, JAK Suykens
2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD), 1-6, 2014
102014
Improved microarray-based decision support with graph encoded interactome data
A Daemen, M Signoretto, O Gevaert, JAK Suykens, B De Moor
PloS one 5 (4), e10225, 2010
102010
Automatic seizure detection incorporating structural information
B Hunyadi, M De Vos, M Signoretto, J Suykens, W Van Paesschen, ...
International Conference on Artificial Neural Networks (ICANN), 233-240, 2011
72011
Kernel-based learning from infinite dimensional 2-way tensors
M Signoretto, L De Lathauwer, JAK Suykens
International Conference on Artificial Neural Networks, 59-69, 2010
72010
Classification of structured EEG tensors using nuclear norm regularization: improving P300 classification
B Hunyadi, M Signoretto, S Debener, S Van Huffel, M De Vos
2013 International Workshop on Pattern Recognition in Neuroimaging, 98-101, 2013
62013
Semi-supervised learning of sparse linear models in mass spectral imaging
F Ojeda, M Signoretto, R Van de Plas, E Waelkens, B De Moor, ...
IAPR International Conference on Pattern Recognition in Bioinformatics, 325-334, 2010
62010
Convex estimation of cointegrated VAR models by a nuclear norm penalty
M Signoretto, JAK Suykens
IFAC Proceedings Volumes 45 (16), 95-100, 2012
52012
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Articles 1–20