Training support vector machines (SVM) with indefinite kernels has recently attracted attention in the machine learning community. This is partly due to the fact that many similarity functions that arise in practice are not symmetric positive semidefinite, i.e. the Mercer condition is not satisfied, or the Mercer condition is difficult to verify. Previous work on training SVM with indefinite ke...

1. I N T R O D U C T I O N Global optimization of constrained quadratic problems has been the subject of active research during the last two decades. Quadratic programming is a very old and important problem of optimization. It has numerous applications in many diverse fields of science and technology and plays a key role in many nonlinear programming methods. Nonconvex quadratic programming re...

We detail the implementation of basic operations on multivariate Chebyshev approximations. In most cases, they can be derived directly from well known properties of univariate Chebyshev polynomials. Besides addition, subtraction and multiplication, we discuss integration, indefinite di↵erentiation, indefinite integration and interpolation. The latter three, can be written as matrix-vector produ...

We consider minimization of a quadratic objective function subject to a sign-indefinite quadratic equality constraint. We derive necessary and sufficient conditions for the existence of solutions to the constrained minimization problem. These conditions involve a generalized eigenvalue of the matrix pencil consisting of a symmetric positivesemidefinite matrix and a symmetric indefinite matrix. ...

This paper considers dynamic optimization problems for a class of control average meanfield stochastic large-population systems. For each agent, the state system is governed by linear mean-field differential equation with individual noise and common noise, weight coefficients in corresponding cost functional can be indefinite. The decentralized optimal strategies are characterized Hamiltonian s...

Decision Support System is playing an important role in computer science, technology and engineering. Intelligent decision-making is one of the current hotspots in the decision support system research. Intelligent decisionmaking methods and algorithms are one of the most important basics and key cores in intelligent information processing, intelligent pervasive computing and so on. In this pape...

the aim of the present study was the estimation of (co) variance components and genetic parameters for body weight of moghani sheep, using random regression models based on b-splines functions. the data set included 9165 body weight records from 60 to 360 days of age from 2811 moghani sheep, collected between 1994 to 2013 from jafar-abad animal research and breeding institute, ardabil province,...