Domain adaptation

A system comprising:

• a processing unit;
• and
• a memory coupled to the processing unit and storing instructions thereon, the instructions, when executed by the processing unit, performing actions comprising:
• obtaining a source model of a source domain, wherein the source model is trained to generate a label indicating a predicted category of first data from the source domain;
• obtaining a training sample from a target domain, wherein the training sample comprises training data from the target domain and a true label indicating a true category of the training data from the target domain;
• generating a first label for the training data by using the source model, wherein the first label indicates a predicted category of the training data;
• and
• training a target model of the target domain based on the training data, the true label and the first label, wherein the target model is trained to generate a label indicating a predicted category of second data from the target domain.

A computer program product being tangibly stored on a non-transient machine-readable medium and comprising machine-executable instructions, the instructions, when executed on a device, causing the device to perform actions comprising:

• obtaining a source model of a source domain, wherein the source model is trained to generate a label indicating a predicted category of first data from the source domain;
• obtaining a training sample from a target domain, wherein the training sample comprises training data from the target domain and a true label indicating a true category of the training data from the target domain;
• generating a first label for the training data by using the source model, wherein the first label indicates a predicted category of the training data;
• and
• training a target model of the target domain based on the training data, the true label and the first label, wherein the target model is trained to generate a label indicating a predicted category of second data from the target domain.