Pinterest, Inc.

Jiajing Xu

Ashim Datta

Kevin McLaughlin

Javier Llaca Ojinaga

Andrei Curelea

Erzhuo Wang

Dz-Mou Jung

Xi Liu

Systems and methods are presented for training a second machine learning model according to aspects of a trained first machine learning model. Processing features utilized by a training framework to train the first machine learning model are identified, and at least some of the processing features are combined with an initial set of training features to form updated training features. The updated training features are presented to a user for customization, resulting in customized training features. An executable training framework is configured with the customized training features and executed to train the second machine learning model.

Accelerated training of a machine learning model

Described are systems and methods for determining a diversity function in connection with potential advertisements in determining one or more advertisements to present to a user. This can facilitate presenting diverse advertisements to users. The diversity function can yield a diversity penalty for each potential advertisement to be able to determine a rank order of the potential advertisements. The diversity function can include a repetition score and a multiplier for each potential advertisement.

Systems and methods for determining a diversity penalty in connection with selecting advertisement content

A system for visual discovery is disclosed. The system identifies a visual search query in response to an action associated with an image presented to a user of a client device. The system extracts visual features from the visual search query and compares the visual features with visual features of stored content items. The system then identifies a set of candidate visual content items from the stored content items that have visual features, which are similar to the visual features of the visual search query. The candidate visual content items are ranked using information from a user session and provided for display to the user.

Identifying content related to a visual search query

Growing community of inventors

Palo Alto, CA, United States of America

Jiajing Xu