Abstract: A new transformation which converts a multivariable positive real function to another multivariable positive real function is presented and the conditions for the reduction in degree of the ...

Abstract: Far function difference approximation is one of the most active research contents in function approximation theory at present. Compared with unary function approximation, there are many ...

Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...

Learn to choose coordinate systems, visualize multivariable functions, and parameterize curves. You can use these live scripts as demonstrations in lectures, class activities, or interactive ...

Solving optimisation problems is a promising near-term application of quantum computers. Quantum variational algorithms (QVAs) leverage quantum superposition and entanglement to optimise over ...

mvsp is a Python implementation of the protocols presented in Quantum state preparation for multivariate functions. The protocols are based on function approximations with finite Fourier or Chebyshev ...

Researchers lift FSS from unary to multivariate: two-layer OT-linked binary trees shrink distributed comparison function key size from O(λn²) to O(λn) ...

ABSTRACT: Piyavskii’s algorithm maximizes a univariate function satisfying a Lipschitz condition. We propose a modified Piyavskii’s sequential algorithm which maximizes a univariate differentiable ...