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:
Jun. 18, 2024

Filed:

Dec. 09, 2020
Applicant:

New York University, New York, NY (US);

Inventor:

Bhubaneswar Mishra, Great Neck, NY (US);

Assignee:

NEW YORK UNIVERSITY, New York, NY (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G07F 17/32 (2006.01); G06N 3/04 (2023.01); G06N 3/044 (2023.01); G06N 3/08 (2023.01); G06Q 10/06 (2023.01); G06Q 10/0639 (2023.01); G06Q 10/067 (2023.01); G06Q 20/06 (2012.01); G06Q 40/04 (2012.01); G16H 40/20 (2018.01); G16H 50/20 (2018.01); G16H 70/20 (2018.01); G06Q 30/0645 (2023.01); G06Q 40/02 (2023.01);
U.S. Cl.
CPC ...
G07F 17/3295 (2013.01); G06N 3/044 (2023.01); G06N 3/08 (2013.01); G06Q 10/06395 (2013.01); G06Q 10/067 (2013.01); G06Q 20/0655 (2013.01); G06Q 40/04 (2013.01); G07F 17/3225 (2013.01); G07F 17/3276 (2013.01); G06Q 30/0645 (2013.01); G06Q 40/02 (2013.01); G06Q 2220/00 (2013.01);
Abstract

An exemplary system, method, and computer-accessible medium for recommending a model(s), can include, for example, receiving a plurality of test models including the model(s), determining if each of the test models has at least one verifier associated therewith, and recommending the model(s) based on the determination. An indication of a stake associated with each of the test models can be received. The stake can be a financial stake or a reputation stake. The financial stake can be a cryptocurrency. At least one of the test models can be analyzed using a machine learning procedure, which can be a convolutional neural network or a recurrent neural network. At least one of the test models can be analyzed using an empirical Bayes procedure. A particular model can be removed if the particular model(s) does not have a verifier(s) associated therewith.


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