US Patent 11188823 Training a neural network using another neural network

In an example embodiment, a first DCNN is trained to output a value for a first metric by inputting a plurality of sample documents to the first DCNN, with each of the sample documents having been labeled with a value for the first metric. Then a plurality of possible transformations of a first input document are fed to the first DCNN, obtaining a value for the first metric for each of the plurality of possible transformations. A first transformation is selected from the plurality of possible transformations based on the values for the first metric for each of the plurality of possible transformations. Then a second DCNN is trained to output a transformation for a document by inputting the selected first transformation to the second DCNN. The second input document is fed to the second DCNN, obtaining a second transformation of the second input document.