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:
Jan. 17, 2023

Filed:

Nov. 26, 2019
Applicant:

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

Inventors:

Andrea Giovannini, Zurich, CH;

Georgios Chaloulos, Zurich, CH;

Frederik Frank Flother, Schlieren, CH;

Patrick Lustenberger, Herrliberg, CH;

David Mesterhazy, Nuremberg, DE;

Stefan Ravizza, Wallisellen, CH;

Eric Slottke, Zurich, CH;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G06N 7/005 (2013.01); G06N 20/00 (2019.01);
Abstract

Aspects of the present invention disclose a method for verifying labels of records of a dataset. The records comprise sample data and a related label out of a plurality of labels. The method includes one or more processors dividing the dataset into a training dataset comprising records relating to a selected label and an inference dataset comprising records with sample data relating to the selected label and all other labels out of the plurality of labels. The method further includes dividing the training dataset into a plurality of learner training datasets that comprise at least one sample relating to the selected label. The method further includes training a plurality of label-specific few-shot learners with one of the learner training datasets. The method further includes performing inference by the plurality of trained label-specific few-shot learners on the inference dataset to generate a plurality of sets of predicted label output values.


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