hessians

we calculated the hessians to optimize the model parameters.

the second derivatives, or hessians, indicated a local minimum.

analyzing the hessians helped us understand the curvature of the surface.

the positive definite hessians confirmed the convexity of the function.

we used the inverse of the hessians for newton's method.

the hessians provided information about the function's behavior.

estimating the hessians is computationally expensive.

we approximated the hessians using finite difference methods.

the eigenvalues of the hessians reveal important properties.

we compared the hessians across different iterations.

the vanishing of hessians suggests a saddle point.