Reach and frequency prediction for digital component transmissions

A system comprising:

• one or more computers;
• and
• one or more storage devices communicatively coupled to the one or more computers, wherein the one or more storage devices store instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising:
• obtaining a plurality of observed frequency histograms that each correspond to a respective observed transmission commitment, wherein:
• a transmission commitment corresponds to a subset of publishers from a set of publishers and specifies, for each publisher in the subset publishers, a number of transmissions of a digital component by way of the publisher, and
• a frequency histogram corresponding to the transmission commitment defines, for each of a plurality of frequency values, a respective number of users who received a number of transmissions of the digital component given by the frequency value when the digital component is transmitted in accordance with the transmission commitment;
• generating a frequency model based on the plurality of observed frequency histograms, wherein:
• the frequency model is a parametric model parameterized by a set of model parameters,
• the frequency model is configured to process an input defining an input transmission commitment to generate an output that defines a predicted frequency histogram corresponding to the input transmission commitment, and
• generating the frequency model comprises training the set of model parameters of the frequency model, using a numerical optimization technique, to optimize an objective function that depends on the observed frequency histograms;
• receiving a request to predict a frequency histogram for a target transmission commitment corresponding to a target subset of publishers;
• and
• in response to receiving the request:
• generating a predicted frequency histogram for the target transmission commitment using the frequency model;
• and
• generating one or more predictions characterizing the target transmission commitment using the predicted frequency histogram.

One or more non-transitory computer storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

• obtaining a plurality of observed frequency histograms that each correspond to a respective observed transmission commitment, wherein:
• a transmission commitment corresponds to a subset of publishers from a set of publishers and specifies, for each publisher in the subset publishers, a number of transmissions of a digital component by way of the publisher, and
• a frequency histogram corresponding to the transmission commitment defines, for each of a plurality of frequency values, a respective number of users who received a number of transmissions of the digital component given by the frequency value when the digital component is transmitted in accordance with the transmission commitment;
• generating a frequency model based on the plurality of observed frequency histograms, wherein:
• the frequency model is a parametric model parameterized by a set of model parameters,
• the frequency model is configured to process an input defining an input transmission commitment to generate an output that defines a predicted frequency histogram corresponding to the input transmission commitment, and
• generating the frequency model comprises training the set of model parameters of the frequency model, using a numerical optimization technique, to optimize an objective function that depends on the observed frequency histograms;
• receiving a request to predict a frequency histogram for a target transmission commitment corresponding to a target subset of publishers;
• and
• in response to receiving the request:
• generating a predicted frequency histogram for the target transmission commitment using the frequency model;
• and
• generating one or more predictions characterizing the target transmission commitment using the predicted frequency histogram.