System and method for enriching datasets while learning

Inactive Publication Date: 2018-11-22
ALLEGRO ARTIFICIAL INTELLIGENCE LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0011]In some embodiments, personalized quality assurance of inference models may be performed. For example, data items associated with a group of devices may be obtained, results of applying the data items to inference models may be obtained, the results of applying the data items to a first inference model may be compared with the results of applying the data items to a second inference model, and the compatibility of the second inference

Problems solved by technology

In some examples, when the second inference model is found incompatible, the system may forgo the usage of the second inference model in one or more tasks as

Method used

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  • System and method for enriching datasets while learning
  • System and method for enriching datasets while learning
  • System and method for enriching datasets while learning

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[0038]Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as “processing”, “calculating”, “computing”, “determining”, “generating”, “setting”, “configuring”, “selecting”, “defining”, “applying”, “obtaining”, “monitoring”, “providing”, “identifying”, “segmenting”, “classifying”, “analyzing”, “associating”, “extracting”, “storing”, “receiving”, “transmitting”, or the like, include action and / or processes of a computer that manipulate and / or transform data into other data, said data represented as physical quantities, for example such as electronic quantities, and / or said data representing the physical objects. The terms “computer”, “processor”, “controller”, “processing unit”, “computing unit”, and “processing module” should be expansively construed to cover any kind of electronic device, component or unit with data processing capabilities, including, by way of non-limiti...

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Abstract

Systems and methods for enriching datasets while learning are provided. For example, intermediate results of training machine learning algorithms may be obtained. Additional training examples may be selected based on the intermediate results. In some cases, synthetic examples may be generated based on the intermediate results. The machine learning algorithms may be further trained using the selected additional training examples and/or the generated synthetic examples.

Description

CROSS REFERENCES TO RELATED APPLICATIONS[0001]This application claims the benefit of priority of U.S. Provisional Patent Application No. 62 / 539,334, filed on Jul. 31, 2017, U.S. Provisional Patent Application No. 62 / 562,398, filed on Sep. 23, 2017, U.S. Provisional Patent Application No. 62 / 562,401, filed on Sep. 23, 2017, U.S. Provisional Patent Application No. 62 / 581,744, filed on Nov. 5, 2017, and U.S. Provisional Patent Application No. 62 / 610,290, filed on Dec. 26, 2017. The entire contents of all of the above-identified applications are herein incorporated by reference.BACKGROUNDTechnological Field[0002]The disclosed embodiments generally relate to systems and methods for dataset management. More particularly, the disclosed embodiments relate to systems and methods for enriching datasets while learning.Background Information[0003]Computerized devices are now prevalent, and data produced and maintained by those devices is increasing.[0004]Audio sensors are now part of numerous d...

Claims

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Application Information

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IPC IPC(8): G06N3/08G06N5/04G06N20/00
CPCG06N3/08G06N5/04H04L63/0823G06N3/082G06N3/084G06N20/10G06F21/6218H04L63/102G06F16/285G06Q10/06311G06N20/00G06N3/048G06N3/044G06N3/045G06F16/2379G06F16/24565G06F18/214G06F18/217G06N7/01H04N23/661G06N5/022G06N5/046G06F7/14G06F9/505
InventorGUTTMANN, MOSHEBILLER, ARIEL YOSSEF
OwnerALLEGRO ARTIFICIAL INTELLIGENCE LTD