Implementing numerical optimization techniques (Gradient Descent, Conjugate Gradient, Nelder-Mead, BFGS) in R for (1.) univariate optimization, (2.) multivariate optimization, (3.) visualizing ...

Keywords: multivariate polynomial, numerical optimization, tensor decomposition, Gauss-Newton algorithm, factorization machines, higher order factorization machines, tensor network, image ...

This paper presents a multivariate optimization technique for the numerical simulation of continuous dynamical systems whose parameters, functional forms and/or initial conditions are modelled by ...

Article citations More>> Varshney, R., Najmussehar and Ahsan, M.J. (2012) An Optimum Multivariate Stratified Double Sampling Design in Presence of Non-Response. Optimization Letters, 6, 993-1008. has ...

This paper describes a parameter estimation algorithm applicable for the model structures in the form of multivariate polynomial systems. An example of a synchronous machine nonlinear model is used ...

Since these maps are submodular (or supermodular) under some assumptions 1, we design greedy-based optimization algorithms with theoretical guarantees. We also perform numerical experiments on ...

With the advent of massively parallel computing coprocessors, numerical optimization for deep-learning disciplines is now possible. Complex real-time pattern recognition, for example, that can be used ...

However, the multivariate procedures that are most commonly applied in numerical ecology do not satisfy these requirements and are therefore not recommended. For example, it is inappropriate to ...

We first show how to solve an attacker-operator (AO) model, then how to use this as a submodel to solve a DAO model. A numerical example illustrates planning defense and operation of a U.S. military ...

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