Google Inc.

Da-Cheng Juan

Andrew Stephen Tomkins

Sujith Ravi

Thomas J Duerig

Zhen Li

Futang Peng

Chun-Ta Lu

Aleksei Timofeev

Yi-ting Chen

Yaxi Gao

Liu Yang

Dara Bahri

Donald Arthur Metzler, Jr

Yi Tay

A system for performing a machine learning task on a network input is described. The system includes one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to implement (i) multiple sorting networks in which each sorting network is configured to sort vector blocks in a sequence of vector blocks to generate a sorted sequence of vector blocks; and (ii) a sorting attention neural network configured to perform the machine learning task on the input sequence by executing multiple sorting attention mechanisms using the sorting networks.

Sorting attention neural networks

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image embedding model. In one aspect, a method comprises: obtaining training data comprising a plurality of training examples, wherein each training example comprises: an image pair comprising a first image and a second image; and selection data indicating one or more of: (i) a co-click rate of the image pair, and (ii) a similar-image click rate of the image pair; and using the training data to train an image embedding model having a plurality of image embedding model parameters.

Training image and text embedding models

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Sunnyvale, CA, United States of America

Da-Cheng Juan