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- Alberto Sorrentino, Lauri Parkkonen, Annalisa Pascarella, Cristina Campi, Michele Piana
- Human brain mapping
- 2009

We present a Bayesian filtering approach for automatic estimation of dynamical source models from magnetoencephalographic data. We apply multi-target Bayesian filtering and the theory of Random Finite Sets in an algorithm that recovers the life times, locations and strengths of a set of dipolar sources. The reconstructed dipoles are clustered in time and… (More)

- Lorenzo Rosasco, Ernesto De Vito, Andrea Caponnetto, Michele Piana, Alessandro Verri
- Neural Computation
- 2004

In this letter, we investigate the impact of choosing different loss functions from the viewpoint of statistical learning theory. We introduce a convexity assumption, which is met by all loss functions commonly used in the literature, and study how the bound on the estimation error changes with the loss. We also derive a general result on the minimizer of… (More)

Two psychophysics experiments are described, pointing out the significant role played by stochastic resonance in recognition of capital stylized noisy letters by the human perceptive apparatus. The first experiment shows that an optimal noise level exists at which the letter is recognized for a minimum threshold contrast. A simple two-parameter model that… (More)

- Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Michele Piana, Alessandro Verri
- Journal of Machine Learning Research
- 2004

In regularized kernel methods, the solution of a learning problem is found by minimizing func-tionals consisting of the sum of a data and a complexity term. In this paper we investigate some properties of a more general form of the above functionals in which the data term corresponds to the expected risk. First, we prove a quantitative version of the… (More)

- Mauro C. Beltrametti, Anna Maria Massone, Michele Piana
- SIAM J. Imaging Sciences
- 2013

- Riccardo Aramini, Massimo Brignone, Joe Coyle, Michele Piana
- SIAM J. Scientific Computing
- 2008

The linear sampling method is a qualitative procedure for the visualization of both impenetrable and inhomogeneous scatterers, which requires the regularized solution of a linear ill-posed integral equation of the first kind. An open issue in this technique is the one of determining the optimal scatterer profile from the visualization maps in an automatic… (More)

- Cristina Campi, Annalisa Pascarella, Alberto Sorrentino, Michele Piana
- Comp. Int. and Neurosc.
- 2011

Automatic estimation of current dipoles from biomagnetic data is still a problematic task. This is due not only to the ill-posedness of the inverse problem but also to two intrinsic difficulties introduced by the dipolar model: the unknown number of sources and the nonlinear relationship between the source locations and the data. Recently, we have developed… (More)

- F. Delbary, Massimo Brignone, Giovanni Bozza, Riccardo Aramini, Michele Piana
- SIAM Journal of Applied Mathematics
- 2010

This paper proposes a qualitative approach to the inverse scattering problem of microwave tomography for breast cancer detection. In a 2D framework, the tumor inside the breast is regarded as an unknown scatterer placed inside an inhomogeneous and lossy background, formed by skin and fat. We firstly present in detail the mathematical formulation of the… (More)

- Michio Miyakawa, Kentaroh Orikasa, Mario Bertero, Patrizia Boccacci, Franco Conte, Michele Piana
- IEEE Trans. Med. Imaging
- 2002

Chirp-pulse microwave computerized tomography (CP-MCT) is an imaging modality developed at the Department of Biocybernetics, University of Niigata (Niigata, Japan), which intends to reduce the microwave-tomography problem to an X-ray-like situation. We have recently shown that data acquisition in CP-MCT can be described in terms of a linear model derived… (More)

A two-step reconstruction scheme is introduced to solve fixed frequency inverse scattering problems in Born approximation conditions. The aim of the approach is to achieve super-resolution effects by constraining the inversion method to exploit some a priori knowledge on the scatterer. Therefore, the first step is to apply the linear sampling method to the… (More)