Return value and gradient of the quadratic model at the current iterate: q_k(p) = f_k + (p-x_k)T g_k + 1/2 (p-x_k)T B_k(p-x_k) \nabla q_k(p) = g_k + B_k(p-x_k)
Return value and gradient of the quadratic model at the current iterate: q_k(p) = f_k + (p-x_k)T g_k + 1/2 (p-x_k)T B_k(p-x_k) \nabla q_k(p) = g_k + B_k(p-x_k)
calculates the gradient at a point
calculates the gradient at a point
Lenses provide a way of mapping between two types, which we typically use to convert something to a DenseVector or other Tensor for optimization purposes.
Lenses provide a way of mapping between two types, which we typically use to convert something to a DenseVector or other Tensor for optimization purposes.
calculates the value at a point
calculates the value at a point