The nominal rate is set by a central bank (ECB) that minimises a quadratic
loss function (LF) for the monetary union, without taking into consideration financial stability:
Compared with [16], we adopt the [L.sub.2,q] norm instead of Frobenius norm in
loss function to reduce the influence of noise and edge information.
We use [L.sub.2,1] matrix norm based
loss function as the reconstruction loss.
These methods require the use of a
loss function, which measures the difference between the parameter and its estimator.
A general classifier is usually trained from supervised learning, which focuses on teaching the label information to the classifier and minimizes the designed
loss function; therefore, it has learned specific feature mapping for each object.
Figures 13 and 14 compare and analyze the change of
loss function value under different learning rates in the whole training process and make a brief analysis and explanation.
The propagation
loss function represents the variation in that range, and the correlation distance will be short because the
loss function has more fluctuation as distance change.
To train the DNN, we used the mean square error (MSE)
loss function to measure the error between the predicted, and the truth vertex positions:
Assuming that the target value of Q is denoted by y, thus the
loss function of Q-network is yielded: