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In this work we design a general method for proving moment inequalities for polynomials of independent random variables. Our method works for a wide range of random variables incl...
We present an algorithm for computing the probability density function of the product of two independent random variables, along with an implementation of the algorithm in a compu...
New families of Fisher information and entropy power inequalities for sums of independent random variables are presented. These inequalities relate the information in the sum of n ...
The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have...
Angelika Kimmig, Bart Demoen, Luc De Raedt, V&iacu...
We survey a few concentration inequalities for submodular and fractionally subadditive functions of independent random variables, implied by the entropy method for self-bounding f...
A generalized dice model for the pairwise comparison of non-necessarily independent random variables is established. It is shown how the transitivity of the probabilistic relation...
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Concentration inequalities deal with deviations of functions of independent random variables from their expectation. In the last decade new tools have been introduced making it pos...
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
We prove the following inequality: for every positive integer n and every collection X1, . . . , Xn of nonnegative independent random variables that each has expectation 1, the pr...