Diffusion Estimation Over Cooperative Multi-Agent Networks With Missing Data
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The report deals with the novel application of Support Vector Machines (Support Vectore Classification and Support Vector Regression) for the analysis and modelling of reservoir data. 2 problems are considered: classification and mapping of porosity data. ...
The paper presents Kernel Ridge Regression, a nonlinear extension of the well known statistical model of ridge regression. New insights on the method are also presented. In particular, the connection between ridge regression and local translation-invariant ...
This paper explores the possibility to replace the usual thresholding decision rule of log likelihood ratios used in speaker verification systems by more complex and discriminant decision functions based for instance on Linear Regression models or Support ...
The problem of reconstructing an unknown signal from n noisy samples can be addressed by means of nonparametric estimation techniques such as Tikhonov regularization, Bayesian regression and state-space fixed-interval smoothing. The practical use of thes ...
This paper explores the possibility to replace the usual thresholding decision rule of log likelihood ratios used in speaker verification systems by more complex and discriminant decision functions based for instance on Linear Regression models or Support ...
Deals with the problem of worst-case parameter estimation in the presence of bounded uncertainties in a linear regression model. The problem has been formulated and solved in Chandrasekaran et al. (1997). It distinguishes itself from other estimation schem ...
A regression problem amounts to the reconstruction of a multi-dimensional hypersurface from a finite number of noisy samples. In modern engineering regression algorithms play a fundamental role due to their capability of inferring mathematical models of ph ...
