Training a model to predict likelihoods of users performing an action after being presented with a content item

A non-transitory computer-readable medium configured to store code comprising instructions, wherein the instructions, when executed by one or more processors of a computer system, cause the one or more processors to:

• display one or more content items to a first user;
• measure a first number of interactions performed by the first user after the one or more content items are displayed to the first user;
• measure a second number of interactions performed by a second user when none of the one or more content items are displayed to the second user;
• determine a measured difference between the first number of interactions and the second number of interactions;
• access a user interaction model that comprises a plurality of layers of a neural network, wherein the user interaction model is trained by:
• applying the user interaction model to generate a predicted difference, the predicted difference indicating a difference between a first predicted number of interactions performed by the first user after the one or more content items are displayed to the first user and a second predicted number of the interaction performed by the second user when none of the one or more content items are displayed to the second user, and
• backpropagating one or more error terms obtained from one or more loss functions to update a set of parameters of the user interaction model, the backpropagating performed through the neural network and one or more of the error terms based on the measured difference and the predicted difference;
• identify an opportunity to display content items to an additional user;
• apply the user interaction model to determine a predicted value of the additional user when a particular content item is displayed to the additional user;
• determine, using the predicted value, whether to display the particular content item to the additional user;
• and
• cause, based on determining to display the particular content item to the additional user, the particular content item to be displayed to the additional user.

A system comprising:

• one or more processors;
• and
• memory configured to store code comprising instructions, wherein the instructions, when executed by the one or more processors, cause the one or more processors to:
• display one or more content items to a first user;
• measure a first number of interactions performed by the first user after the one or more content items are displayed to the first user;
• measure a second number of interactions performed by a second user when none of the one or more content items are displayed to the second user;
• determine a measured difference between the first number of interactions and the second number of interactions;
• access a user interaction model that comprises a plurality of layers of a neural network, wherein the user interaction model is trained by:
• applying the user interaction model to generate a predicted difference, the predicted difference indicating a difference between a first predicted number of interactions performed by the first user after the one or more content items are displayed to the first user and a second predicted number of the interaction performed by the second user when none of the one or more content items are displayed to the second user, and
• backpropagating one or more error terms obtained from one or more loss functions to update a set of parameters of the user interaction model, the backpropagating performed through the neural network and one or more of the error terms based on the measured difference and the predicted difference;
• identify an opportunity to display content items to an additional user;
• apply the user interaction model to determine a predicted value of the additional user when a particular content item is displayed to the additional user;
• determine, using the predicted value, whether to display the particular content item to the additional user;
• and
• cause, based on determining to display the particular content item to the additional user, the particular content item to be displayed to the additional user.