Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for displaying digital components on client devices based on predicted user attributes of users are described. In one aspect, a method includes updating, at a client device of a user, a list of user group identifiers for the user to include a particular user group identifier that identifies a particular user group. A determination is made, for each user attribute of multiple user attributes, a score based on a quantity of user groups identified in the list of group identifiers for the user that include, as a membership attribute, the user attribute. A digital component request including data representing the list of user-group identifiers is sent to a content distribution system. Digital component data identifying a set of digital components selected based on the data of the digital component request is received.

Abstract: The present disclosure describes techniques for training a model using cross-domain adaptation to classify content requests from client devices having unknown attributes. The system can obtain requests for content from client devices of a first domain, and requests for content from client devices of a second domain. The system can train a model by propagating request attributes of the first domain through the model to generate first internal data from an internal layer of the model and a first output vector an output layer of the model. The system can propagate request attributes of the second domain to generate second internal data, and determine a difference between the first internal data and the second internal data. The system can update the model based on the difference and the output vector, and classify a third client device of the second domain using the model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for displaying digital components on client devices based on predicted user attributes of users are described. In one aspect, a method includes updating, at a client device of a user, a list of user group identifiers for the user to include a particular user group identifier that identifies a particular user group. A determination is made, for each user attribute of multiple user attributes, a score based on a quantity of user groups identified in the list of group identifiers for the user that include, as a membership attribute, the user attribute. A digital component request including data representing the list of user-group identifiers is sent to a content distribution system. Digital component data identifying a set of digital components selected based on the data of the digital component request is received.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing digital components to a client device. Methods can include assigning a temporary group identifier to a client device that identifies a particular group, from among a plurality different groups, that includes the client device based on a current period of user activity on the client device. A training set is generated for training a machine learning model that generates user characteristics. A request for digital component is received from the client device that includes the temporary group identifier currently assigned to the client device, a subset of activity features and one or more additional features that are based on the client device. The machine learning model generates one or more user characteristics based on which one or more digital components are selected and transmitted to the client device.