Learning unified embedding

A system for generating a unified machine learning model using a neural network, the system comprising:

• a data processing apparatus configured to implement the neural network, the data processing apparatus including one or more processing devices;
• and
• one or more non-transitory machine-readable storage devices storing instructions that are executable by the one or more processing devices to cause performance of operations comprising:
• determining, by the data processing apparatus and for the neural network, respective learning targets for each of a plurality of object verticals, wherein each object vertical defines a distinct category for an object that belongs to the vertical;
• training, by the data processing apparatus and based on a first loss function, the neural network to identify data associated with each of the plurality of object verticals, where the neural network is trained using the respective learning targets;
• and
• generating, by the data processing apparatus and using the neural network trained based on the first loss function, a unified machine learning model configured to identify items that are included in the data associated with each of the plurality of object verticals.

One or more non-transitory machine-readable storage devices storing instructions that are executable by the one or more processing devices to generate a unified machine learning model and to cause performance of operations comprising:

• determining, by a data processing apparatus configured to implement the neural network, respective learning targets for each of a plurality of object verticals, wherein each object vertical defines a distinct category for an object that belongs to the vertical;
• training, by the data processing apparatus and based on a first loss function, the neural network to identify data associated with each of the plurality of object verticals, where the neural network is trained using the respective learning targets;
• and
• generating, by the data processing apparatus and using the neural network trained based on the first loss function, a unified machine learning model configured to identify items that are included in the data associated with each of the plurality of object verticals.