CLASSIFYING DATA OBJECTS USING NEIGHBORHOOD REPRESENTATIONS

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying data objects. One of the methods includes maintaining a dataset comprising a plurality of reference data objects that each have one or more labels, one or more features, or both; receiving a request to add, to the dataset, a new data object that has one or more features but is missing one or more labels; selecting N neighbor data objects based on similarity scores of the neighbor data objects with respect to the new data object; generating a neighborhood feature vector for the new data object; processing the neighborhood feature vector using a machine learning model to predict the one or more labels for the new data object; and updating the dataset to include the new data object and to associate the one or more predicted labels with the new data object.