minimax loss
A loss function for generative adversarial networks, based on the cross-entropy between the distribution of generated data and real data.
Plain English Explanation
A loss function for generative adversarial networks, based on the cross-entropy between the distribution of generated data and real data. Minimax loss is used in the first paper to describe generative adversarial networks. See Loss Functions in the Generative Adversarial Networks course for more information.
How is it used?
Practitioners refer to minimax loss when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.