The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 29, 2024

Filed:

Sep. 16, 2020
Applicant:

Baidu Usa, Llc, Sunnyvale, CA (US);

Inventors:

Shulong Tan, Santa Clara, CA (US);

Zhixin Zhou, Los Angeles, CA (US);

Zhaozhuo Xu, Houston, TX (US);

Ping Li, Bellevue, WA (US);

Assignee:

Baidu USA LLC, Sunnyvale, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 16/901 (2019.01); G06F 16/33 (2019.01); G06F 18/2413 (2023.01);
U.S. Cl.
CPC ...
G06F 16/9024 (2019.01); G06F 16/3347 (2019.01); G06F 18/24147 (2023.01);
Abstract

Retrieval of relevant vectors produced by representation learning can critically influence the efficiency in Natural Language Processing (NLP) tasks. Presented herein are systems and methods for searching vectors via a typical nonmetric matching function: inner product. Embodiments, which construct an approximate Inner Product Delaunay Graph (IPDG) for top-1 Maximum Inner Product Search (MIPS), transform retrieving the most suitable latent vectors into a graph search problem with great benefits of efficiency. Experiments on data representations learned for different machine learning tasks verify the outperforming effectiveness and efficiency of IPDG embodiments.


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