Machine learning based file ranking methods and systems

A system, comprising:

• a plurality of artificial neural networks (ANNs);
• and
• a processor configured to be coupled to the plurality of ANNs and configured to execute a loss layer, the processor further configured to:
• receive, via the loss layer, a plurality of ANN output pairs, each ANN output pair from the plurality of ANN output pairs associated with a different label from a plurality of labels;
• generate, via the loss layer, a mask after calculating a loss value based on an activation function and based on the plurality of ANN output pairs, the generating including, for each portion from a plurality of portions included in the mask:
• for each ANN output pair from the plurality of ANN output pairs and associated with that portion:
• detecting whether a first ANN output of that ANN output pair is preferred over a second ANN output of that ANN output pair,
• in response to detecting a lack of preference between the first ANN output and the second ANN output, setting an indication that that portion of the mask will not cause an adjustment to a label weighting for that ANN output pair, and
• in response to detecting a preference of the first ANN output or the second ANN output, setting an indication that that portion of the mask will cause the adjustment to the label weighting for that ANN output pair;
• and
• send a signal, including the mask, from the processor to a first ANN from the plurality of ANNs and a second ANN for the plurality of ANNs, such that the first ANN and the second ANN collectively update a ranking model hosted by the first ANN and the second ANN in response to the signal.

A non-transitory processor-readable medium storing instructions that, when executed, cause a processor to:

• receive, via a loss layer of the processor and from a plurality of artificial neural networks (ANNs), a plurality of signals representing an associated plurality of ANN output pairs associated with a label;
• define, via the loss layer, a mask, the defining including, (1) for each portion from a plurality of portions included in the mask and (2) for each ANN output pair from the plurality of ANN output pairs and associated with that portion:
• detecting whether a preference exists between a first ANN output of that ANN output pair and a second ANN output of that ANN output pair,
• in response to detecting a lack of preference between the first ANN output and the second ANN output, setting an indication that that portion of the mask will not cause an adjustment to a label weighting for that ANN output pair, and
• in response to detecting a preference of the first ANN output or the second ANN output, setting an indication that that portion of the mask will cause the adjustment to the label weighting for that ANN output pair;
• and
• sending a signal, including a representation of the mask, from the processor to each ANN from the plurality of ANNs, to update a ranking model of the plurality of ANNs in response to the signal.