We consider a quadratic programming (QP) problem (Π) of the form minxCx subject toAx ≥ b where C ∈ R + , rank(C) = 1 and A ∈ R, b ∈ R. We present an FPTAS for this problem by reformulating the QP (Π) as a parametrized LP and “rounding” the optimal solution. Furthermore, our algorithm returns an extreme point solution of the polytope. Therefore, our results apply directly to 0-1 problems for whi...

In the Integer Quadratic Programming problem input is an n× n integer matrix Q, an m × n integer matrix A and an m-dimensional integer vector b. The task is to find a vector x ∈ Z minimizing xQx, subject to Ax ≤ b. We give a fixed parameter tractable algorithm for Integer Quadratic Programming parameterized by n+α. Here α is the largest absolute value of an entry of Q and A. As an application o...

f(x, y) = a x + x Qy + b y, where a, x ∈ R, b, y ∈ R, and Q is a matrix of dimension n ×m. It is easy to see that bilinear functions compose a subclass of quadratic functions. We refer to optimization problems with bilinear objective and/or constraints as bilinear problems, and they can be viewed as a subclass of quadratic programming. Bilinear programming has various applications in constraine...

Total least squares (TLS) is a method for treating an overdetermined system of linear equations Ax ≈ b, where both the matrix A and the vector b are contaminated by noise. Tikhonov regularization of the TLS (TRTLS) leads to an optimization problem of minimizing the sum of fractional quadratic and quadratic functions. As such, the problem is nonconvex. We show how to reduce the problem to a sing...

Ridge regression, being based on the minimization of a quadratic loss function, is sensitive to outliers. Current proposals for robust ridge regression estimators are sensitive to “bad leverage observations”, cannot be employed when the number of predictors p is larger than the number of observations n; and have a low robustness when the ratio p=n is large. In this paper a ridge regression esti...

This article focuses on a recent concept of covariation for processes taking values in a separable Banach space B and a corresponding quadratic variation. The latter is more general than the classical one of Métivier and Pellaumail. Those notions are associated with some subspace χ of the dual of the projective tensor product of B with itself. We also introduce the notion of a convolution type ...

None of the usual floating point numerical techniques available for solving the quadratic matrix equation AX +BX +C = 0 with square matrices A,B, C and X, can provide an exact solution; they can just obtain approximations to an exact solution. We use interval arithmetic to compute an interval matrix which contains an exact solution to this quadratic matrix equation, where we aim at obtaining na...

We present and study the matrix-restricted total least squares (MRTLS) devised to solve linear systems of the form Ax b where A and b are both subjected to noise and A has errors of the form DEC. D and C are known matrices and E is unknown. We show that the MRTLS problem amounts to solving a problem of minimizing a sum of fractional quadratic terms and a quadratic function and compare it to the...

None of the usual floating point numerical techniques available for solving the quadratic matrix equation AX +BX +C = 0 with square matrices A,B, C and X, can provide an exact solution; they can just obtain approximations to an exact solution. We use interval arithmetic to compute an interval matrix which contains an exact solution to this quadratic matrix equation, where we aim at obtaining na...

Thermally-activated flux flow (TAFF) resistivity above the irreversibility field Bi is reported for two different c-axis textured MgB2 superconducting films. Transport measurements at different perpendicular magnetic fields 0,B,9 T and temperatures from 5 to 40 K reveal TAFF Ohmic resistivity rsT ,Bd for B.Bi described by the Arrhenius law, r=r0 exps-U /Td with the quadratic field dependence of...