Google Inc.

Samuel Sze Ming Ieong

Christopher Kenneth Harris

Chenyu Zhao

Di Wang

Vinod Kumar Ramachandran

Shibani Sanan

Nicola Rettke

Anthony Chavez

Sissie Ling-le Hsiao

Aranyak Mehta

Sissie Ling-Ie Hsiao

Bin Liu

Xi Tan

Gabriel Florin Constantin

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a system that controls content distribution using a feedback loop. Content is distributed over multiple different online channels using a same initial selection value for distribution over each different online channel. An observed user actions required for distribution of the content over the multiple different online channels is received through a feedback loop and for multiple different distributions of the content. Based on the observed user actions received through the feedback loop, a predicted user action rate is determined for the multiple different distributions across the multiple different online channels. The selection value is adjusted based on a difference between the predicted user action rate and a reference distribution amount specified by a provider of the content. The content is distributed over the multiple different online channels using the adjusted selection value.

Optimization of a multi-channel system using a feedback loop

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for providing content. Data specifying a post-install activity is received from a provider of an application. An opportunity is identified to provide third-party content to a user. A likelihood is determined that the user will perform the specified post-install activity based on one or more attributes of the user and attributes of users that have previously performed the specified post-install activity in the application. A selection value is adjusted for third-party content that identifies the application based on the determined likelihood, wherein the selection value increases as the likelihood increases. The third-party content identifying the application is selected based on the adjusted selection value. The third-party content identifying the application is distributed to a client device of the user.

Post-install application interaction

Methods, systems, apparatus, including computer programs encoded on a computer storage medium, for determining whether to execute a query based on a predicted computerized rendering period The method may include actions of receiving a query, determining a set of one or more features based on the query, generating a query vector, providing the query vector to a machine learning model, receiving first data, based on the output of the machine learning model, that is indicative of whether the computerized rendering period associated with the query is likely to satisfy the predetermined threshold, determining based on the first data that the computerized rendering period available for displaying a set of one or more candidate content items that are responsive to the query is not likely to satisfy the predetermined threshold, and determining to not use a search engine to execute the received query.

Content search engine

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a system that controls content distribution using a feedback loop. Content is distributed over multiple different online channels using a same initial maximum selection value for distribution over each different online channel. An observed distribution amount required for distribution of the content over the multiple different online channels is received through a feedback loop and for multiple different distributions of the content. Based on the observed distribution amount received through the feedback loop, a realized distribution amount is determined for the multiple different distributions across the multiple different online channels. The maximum selection value is adjusted based on a difference between the realized distribution amount and a reference distribution amount specified by a provider of the content. The content is distributed over the multiple different online channels using the adjusted maximum selection value.

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Mountain View, CA, United States of America

Samuel Sze Ming Ieong