Contour-based loss function for machine learning

Abstract

Systems, apparatuses, and methods for training a machine learning (ML) model. Training the ML model may include using contour lines on a plot of prediction values to expected values to determine loss values indicative of errors between prediction values output by the ML model and corresponding expected values. The contour lines may be associated with loss values. Using the contour lines to determine the loss values may include, for each prediction value-expected value pair: generating a one-dimensional loss function through the prediction value-expected value pair, and using the one-dimensional loss function to determine a loss value for the prediction value-expected value pair. Training the ML model may include using an overall loss function to determine an overall loss of the ML model based on the determined loss values. Training the ML model may include adjusting the ML model to minimize the overall loss of the ML model.

Dependencies are inferred from the claim text.