Marco Signoretto

According to our database1, Marco Signoretto authored at least 18 papers between 2008 and 2015.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 




Kernel Methods.
Proceedings of the Springer Handbook of Computational Intelligence, 2015

Learning with tensors: a framework based on convex optimization and spectral regularization.
Machine Learning, 2014

Hybrid Conditional Gradient - Smoothing Algorithms with Applications to Sparse and Low Rank Regularization.
CoRR, 2014

High level high performance computing for multitask learning of time-varying models.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Big Data, 2014

Nonlinear Acoustic Echo Cancellation Based on a Sliding-Window Leaky Kernel Affine Projection Algorithm.
IEEE Trans. Audio, Speech & Language Processing, 2013

Learning Tensors in Reproducing Kernel Hilbert Spaces with Multilinear Spectral Penalties.
CoRR, 2013

Classification of Structured EEG Tensors Using Nuclear Norm Regularization: Improving P300 Classification.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

DynOpt: Incorporating dynamics into mean-variance portfolio optimization.
Proceedings of the 2013 IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 2013

Classification of Multichannel Signals With Cumulant-Based Kernels.
IEEE Trans. Signal Processing, 2012

Joint Regression and Linear Combination of Time Series for Optimal Prediction.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Kernels and Tensors for Structured Data Modelling (Kernels en tensoren voor het modelleren van gestructureerde data).
PhD thesis, 2011

Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data.
IEEE Signal Process. Lett., 2011

A kernel-based framework to tensorial data analysis.
Neural Networks, 2011

Automatic Seizure Detection Incorporating Structural Information.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging.
Proceedings of the Pattern Recognition in Bioinformatics, 2010

Kernel-Based Learning from Infinite Dimensional 2-Way Tensors.
Proceedings of the Artificial Neural Networks, 2010

Improved non-parametric sparse recovery with data matched penalties.
Proceedings of the 2nd International Workshop on Cognitive Information Processing, 2010

Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation.
Proceedings of the Artificial Neural Networks, 2008