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:
Nov. 07, 2023

Filed:

Nov. 29, 2017
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Pradip Bose, Yorktown Heights, NY (US);

Alper Buyuktosunoglu, White Plains, NY (US);

Schuyler Eldridge, Ossining, NY (US);

Karthik V. Swaminathan, Mount Kisco, NY (US);

Swagath Venkataramani, Yonkers, NY (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/82 (2022.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06F 18/214 (2023.01); G06F 18/20 (2023.01); G06N 3/045 (2023.01); G06V 10/774 (2022.01);
U.S. Cl.
CPC ...
G06V 10/82 (2022.01); G06F 18/214 (2023.01); G06F 18/2148 (2023.01); G06F 18/285 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06V 10/7747 (2022.01);
Abstract

A system includes a determination component that determines output for successively larger neural networks of a set; and a consensus component that determines consensus between a first neural network and a second neural network of the set. A linear chain of increasingly complex neural networks trained on progressively larger inputs is utilized (e.g., increasingly complex neural networks is generally representative of increased accuracy). Outputs of progressively networks are computed until a consensus point is reached—where two or more successive large networks yield a same inference output. At such point of consensus the larger neural network of the set reaching consensus can be deemed appropriately sized (or of sufficient complexity) for a classification task at hand.


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