Sentence examples for by computing the gradient from inspiring English sources

This is achieved by computing the gradient (vec{g}) and the Hessian H (or its approximation) at each iteration of the nonlinear regression.

Further, the traditional way to learn the parameters of a deep architecture is to minimize an objective function by computing the gradient over all the parameters using the backpropagation algorithm [14] with a nonlinear optimizer.

By rewriting the matrix quadratic form in the log-likelihood term of (34) as a vector quadratic form in terms of h ̲ ( f ) and by computing the gradient of Q G and equating it to zero, we obtain h ̲ ( f ) = γ Σ h ̲ − 1 ( f ) + 1 σ b 2 ( f ) ∑ n = 1 N ( R ̂ s ( n, f ) ⊗ I I ) T − 1 × γ Σ h ̲ − 1 ( f ) μ h ̲ ( f ) + 1 σ b 2 ( f ) ∑ n = 1 N vec ( R ̂ xs ( n, f ) ) (35).

Often it is helpful to interpret MEG fields measured by magnetometers (and axial gradiometers, e.g., Gross et al. 2012) after transforming the data to a planar gradient configuration, that is, by computing the gradient tangential to the scalp.

A voxel-wise approximation of the surface normal was obtained by computing the gradient direction for each voxel within a scalar field derived by a combination of these distance functions (ФWM– ФPBS).

It is found that the error in modulus obtained by directly computing the gradient of stress strain curve is relatively small and can be used in analysis.

Ruiz et al. [26] presented a texture orientation detection algorithm by computing the dominant gradient and reducing the unnecessary directional candidate modes in the RDO process, saving average time of 30.1% compared with HM 14.0.

The application of the same LMS algorithm by alternatively computing the gradients with respect to and results in the following update equations: (32).

According to the characteristics of the Cartesian grids, the Kutta condition is applied by specially computing the gradients on Kutta-faces without directly assigning the potential jump to cells adjacent wake faces, which can significantly improve the solution converging speed.

At each conjugate-gradient iteration, it is only involved with computing the gradient of objective function.

Therefore we have chosen to use numerical differentiation for computing the gradient.