26,993 research outputs found

    On the t-Term Rank of a Matrix

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    For t a positive integer, the t-term rank of a (0,1)-matrix A is defined to be the largest number of 1s in A with at most one 1 in each column and at most t 1s in each row. Thus the 1-term rank is the ordinary term rank. We generalize some basic results for the term rank to the t-term rank, including a formula for the maximum term rank over a nonempty class of (0,1)-matrices with the the same row sum and column sum vectors. We also show the surprising result that in such a class there exists a matrix which realizes all of the maximum terms ranks between 1 and t.Comment: 18 page

    Level sets and non Gaussian integrals of positively homogeneous functions

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    We investigate various properties of the sublevel set {x : g(x)≀1}\{x \,:\,g(x)\leq 1\} and the integration of hh on this sublevel set when gg and hhare positively homogeneous functions. For instance, the latter integral reduces to integrating hexp⁑(βˆ’g)h\exp(-g) on the whole space RnR^n (a non Gaussian integral) and when gg is a polynomial, then the volume of the sublevel set is a convex function of the coefficients of gg. In fact, whenever hh is nonnegative, the functional βˆ«Ο•(g(x))h(x)dx\int \phi(g(x))h(x)dx is a convex function of gg for a large class of functions Ο•:R+β†’R\phi:R_+\to R. We also provide a numerical approximation scheme to compute the volume or integrate hh (or, equivalently to approximate the associated non Gaussian integral). We also show that finding the sublevel set {x : g(x)≀1}\{x \,:\,g(x)\leq 1\} of minimum volume that contains some given subset KK is a (hard) convex optimization problem for which we also propose two convergent numerical schemes. Finally, we provide a Gaussian-like property of non Gaussian integrals for homogeneous polynomials that are sums of squares and critical points of a specific function
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