Invention Grant
- Patent Title: Training neural networks to generate structured embeddings
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Application No.: US16586223Application Date: 2019-09-27
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Publication No.: US11494695B2Publication Date: 2022-11-08
- Inventor: Robert Andrew James Clark , Chun-an Chan , Vincent Ping Leung Wan
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Honigman LLP
- Agent Brett A. Krueger; Grant Griffith
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N3/04 ; G06N3/08

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to generate embeddings of inputs to the machine learning model, the machine learning model having an encoder that generates the embeddings from the inputs and a decoder that generates outputs from the generated embeddings, wherein the embedding is partitioned into a sequence of embedding partitions that each includes one or more dimensions of the embedding, the operations comprising: for a first embedding partition in the sequence of embedding partitions: performing initial training to train the encoder and a decoder replica corresponding to the first embedding partition; for each particular embedding partition that is after the first embedding partition in the sequence of embedding partitions: performing incremental training to train the encoder and a decoder replica corresponding to the particular partition.
Public/Granted literature
- US20210097427A1 TRAINING NEURAL NETWORKS TO GENERATE STRUCTURED EMBEDDINGS Public/Granted day:2021-04-01
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