This work proposes and analyzes a sparse grid stochastic collocation method for solving elliptic partial differential equations with random coefficients and forcing terms (input data of the model). This method can be viewed as an extension of the Stochastic Collocation method proposed in [Babuška-Nobile-Tempone, Technical report, MOX, Dipartimento di Matematica, 2005] which consists of a Galerk...

We obtain a tight distribution-specific characterization of the sample complexity of large-margin classification with L2 regularization: We introduce the margin-adapted dimension, which is a simple function of the second order statistics of the data distribution, and show distribution-specific upper and lower bounds on the sample complexity, both governed by the margin-adapted dimension of the ...

The probability density function of Kerr effect phase noise, often called the Gordon-Mollenauer effect, is derived analytically. The Kerr effect phase noise can be accurately modeled as the summation of a Gaussian random variable and a noncentral chi-square random variable with two degrees of freedom. Using the received intensity to correct for the phase noise, the residual Kerr effect phase no...

We show that there can be no finite list of conditional independence relations which can be used to deduce all conditional independence implications among Gaussian random variables. To do this, we construct, for each n > 3 a family of n conditional independence statements on n random variables which together imply that X1⊥X2, and such that no subset have this same implication. The proof relies ...

A difference approximation that is second-order accurate in the time step h is derived for the general Ito stochastic differential equation. The difference equation has the form of a second-order random walk in which the random terms are non-linear combinations of Gaussian random variables. For a wide class of problems, the transition pdf is joint-normal to second order in h; the technique then...

This paper presents a general result for the simulation of correlated heterogeneous targets, which are present in images corrupted by speckle noise. This technique is based on the use of a correlation mask and Gaussian random variables, in order to obtain spatially dependent Gamma deviates. These Gamma random variables, in turn, allow the obtainment of correlated K deviates with specified corre...

We consider Gaussian, Poissonian, fractional Gaussian and fractional Poissonian white noise spaces, all represented through the corresponding orthogonal basis of the Hilbert space of random variables with finite second moments, given by the Hermite and the Charlier polynomials. There exist unitary mappings between the Gaussian and Poissonian white noise spaces. We investigate the relationship o...

Probabilistic Logic Programming (PLP), exemplified by Sato and Kameya’s PRISM, Poole’s ICL, De Raedt et al’s ProbLog and Vennekens et al’s LPAD, combines statistical and logical knowledge representation and inference. Inference in these languages is based on enumerative construction of proofs over logic programs. Consequently, these languages permit very limited use of random variables with con...