Apparatus for Domain Generalization of Machine Learning Models, Methods and Computer Readable Recording Mediums Therefor

Systems and methods for domain generalization configured in accordance with some embodiments of the invention are illustrated. One embodiment includes a method for domain generalization of a machine learning model. The method sets a parameter of a first model and a parameter of a second model based on a pre-trained model. The method learns the second model by performing a predetermined task on a source domain. The method estimates an unobservable gradient for model updates on an unseen domain based on: the parameter of the first model, and the parameter of the second model. The method updates the first model based on the estimated unobservable gradient.