Marco Signoretto

According to our database, Marco Signoretto authored at least 18 papers between 2008 and 2015.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2015

Kernel Methods.

Marco Signoretto, Johan A. K. Suykens

Proceedings of the Springer Handbook of Computational Intelligence, 2015

2014

Learning with tensors: a framework based on convex optimization and spectral regularization.

Marco Signoretto, Dinh Quoc Tran, Lieven De Lathauwer, Johan A. K. Suykens

Mach. Learn., 2014

Hybrid Conditional Gradient - Smoothing Algorithms with Applications to Sparse and Low Rank Regularization.

Andreas Argyriou, Marco Signoretto, Johan A. K. Suykens

CoRR, 2014

High level high performance computing for multitask learning of time-varying models.

Marco Signoretto, Emanuele Frandi, Zahra Karevan, Johan A. K. Suykens

Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Big Data, 2014

2013

Nonlinear Acoustic Echo Cancellation Based on a Sliding-Window Leaky Kernel Affine Projection Algorithm.

Jose Manuel Gil-Cacho, Marco Signoretto, Toon van Waterschoot, Marc Moonen, Søren Holdt Jensen

IEEE Trans. Speech Audio Process., 2013

Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties.

Marco Signoretto, Lieven De Lathauwer, Johan A. K. Suykens

CoRR, 2013

Classification of Structured EEG Tensors Using Nuclear Norm Regularization: Improving P300 Classification.

Borbála Hunyadi, Marco Signoretto, Stefan Debener, Sabine Van Huffel, Maarten De Vos

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

DynOpt: Incorporating dynamics into mean-variance portfolio optimization.

Marco Signoretto, Johan A. K. Suykens

Proceedings of the 2013 IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 2013

2012

Classification of Multichannel Signals With Cumulant-Based Kernels.

Marco Signoretto, Emanuele Olivetti, Lieven De Lathauwer, Johan A. K. Suykens

IEEE Trans. Signal Process., 2012

Joint Regression and Linear Combination of Time Series for Optimal Prediction.

Dries Geebelen, Kim Batselier, Philippe Dreesen, Marco Signoretto, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle

Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011

Kernels and Tensors for Structured Data Modelling (Kernels en tensoren voor het modelleren van gestructureerde data).

Marco Signoretto

PhD thesis, 2011

Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data.

Marco Signoretto, Raf Van de Plas, Bart De Moor, Johan A. K. Suykens

IEEE Signal Process. Lett., 2011

A kernel-based framework to tensorial data analysis.

Marco Signoretto, Lieven De Lathauwer, Johan A. K. Suykens

Neural Networks, 2011

Automatic Seizure Detection Incorporating Structural Information.

Borbála Hunyadi, Maarten De Vos, Marco Signoretto, Johan A. K. Suykens, Wim Van Paesschen, Sabine Van Huffel

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010

Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging.

Fabian Ojeda, Marco Signoretto, Raf Van de Plas, Etienne Waelkens, Bart De Moor, Johan A. K. Suykens

Proceedings of the Pattern Recognition in Bioinformatics, 2010

Kernel-Based Learning from Infinite Dimensional 2-Way Tensors.

Marco Signoretto, Lieven De Lathauwer, Johan A. K. Suykens

Proceedings of the Artificial Neural Networks, 2010

Improved non-parametric sparse recovery with data matched penalties.

Marco Signoretto, Kristiaan Pelckmans, Lieven De Lathauwer, Johan A. K. Suykens

Proceedings of the 2nd International Workshop on Cognitive Information Processing, 2010

2008

Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation.

Marco Signoretto, Kristiaan Pelckmans, Johan A. K. Suykens

Proceedings of the Artificial Neural Networks, 2008