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Google PCA Patent for Large-Scale Data Processing

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Summary

The USPTO granted Patent US12608444B2 to Google LLC for a method of automated selection of principal component analysis (PCA) variants for large-scale datasets. The patent covers receiving a PCA request, training a PCA model on input features, determining principal components, generating embedded features, and returning those features to the user. The patent was filed on July 29, 2022, under application number 17816288, with 14 claims.

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What changed

Google LLC has been granted Patent US12608444B2 by the USPTO covering a method for automated selection of principal component analysis variants for large-scale datasets. The patent encompasses training a PCA model on input features, determining principal components, generating embedded features, and returning those features to the user.

Technology companies and data science practitioners developing large-scale data processing systems may wish to review this patent when designing PCA or dimensionality reduction workflows, as the automated variant selection technique is now protected IP. Competitors developing similar ML-based data processing methods should conduct freedom-to-operate analyses.

Archived snapshot

Apr 21, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Grants

Automated selection of principal component analysis variants for large-scale datasets

Grant US12608444B2 Kind: B2 Apr 21, 2026

Assignee

Google LLC

Inventors

Xi Cheng, Mingge Deng, Amir Hossein Hormati

Abstract

A method for principal component analysis includes receiving a principal component analysis (PCA) request from a user requesting data processing hardware to perform PCA on a dataset, the dataset including a plurality of input features. The method further includes training a PCA model on the plurality of input features of the dataset. The method includes determining, using the trained PCA model, one or more principal components of the dataset. The method also includes generating, based on the plurality of input features and the one or more principal components, one or more embedded features of the dataset. The method includes returning the one or more embedded features to the user.

CPC Classifications

G06F 18/2135 G06F 16/2433 G06F 16/7343 G06N 20/00 G06N 7/00 G06V 10/77 G05B 23/024 H04L 41/024

Filing Date

2022-07-29

Application No.

17816288

Claims

14

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Last updated

Classification

Agency
USPTO
Published
April 21st, 2026
Instrument
Notice
Branch
Executive
Legal weight
Binding
Stage
Final
Change scope
Minor

Who this affects

Applies to
Technology companies
Industry sector
5112 Software & Technology
Activity scope
Patent grant ML data processing Dimensionality reduction
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence Data Privacy

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