Exact(13)
Step 6 is the normal gradient descent step of the original objective function Q V).
The initial descent step size η(0) is simply set to 1.0.
A data-driven procedure that permits a fully automatic selection of the value of the descent step is also proposed.
Initialize the iteration counter (ell=0), the descent step counter (k:=k ell)=0) with (i_{0}=0).
The next recursion not only possesses a more generalized adaptive descent step, but it also can be implemented easily by the relaxed method.
where τ is a scalar that controls the gradient descent step size, and the function η K computes the best K-term approximation of a l+1 (see Algorithm 2).
Similar(47)
As usual in bundle methods, two cases are considered: the algorithm generates finite number of descent steps; and the algorithm generates infinite number of descent steps.
Algorithm 1 generates finite number of descent steps followed by infinitely many null steps.
Then the following mutually exclusive situations hold: (i) Algorithm 1 generates finite number of descent steps followed by infinitely many null steps.
Following this model, in order to fit the digital image, a cubic spline representation is being utilized to perform gradient descent steps, while maintaining interpolation at some initial (manually sampled) points.
Because we chose the batch randomly in every step, the different training batch sets between the continues gradient descent steps led the apparent fluctuation in Fig. 4 in both of the environments.
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