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公开(公告)号：US10685645B2
公开(公告)日：2020-06-16
申请号：US16059189
申请日：2018-08-09
Applicant: Bank of America Corporation
Inventor： Maruthi Z. Shanmugam , Luis Gerardo Mojica de la Vega , Donatus Asumu
Abstract: A method for creating binary classification models and using the binary classification models to select candidate training utterances from a plurality of live utterances is provided. The method may include receiving a plurality of intents and associated training utterances. The method may include creating, from the training utterances, a binary classification model for each intent. The binary classification model may include a vector representation of a line of demarcation between utterances associated with the intent and utterances disassociated from the intent. The method may also include receiving live utterances. An intent may be determined for each live utterance. The method may include creating a vector representation of the live utterance. The method may include selecting candidate training utterances based on a comparison between the vector representation of the live utterance and the vector representation included in the binary classification model of the intent determined for the live utterance.
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2.发明申请公开(公告)号：US20200051547A1
公开(公告)日：2020-02-13
申请号：US16059189
申请日：2018-08-09
Applicant: Bank of America Corporation
Inventor： Maruthi Z. Shanmugam , Luis Gerardo Mojica de la Vega , Donatus Asumu
Abstract: A method for creating binary classification models and using the binary classification models to select candidate training utterances from a plurality of live utterances is provided. The method may include receiving a plurality of intents and associated training utterances. The method may include creating, from the training utterances, a binary classification model for each intent. The binary classification model may include a vector representation of a line of demarcation between utterances associated with the intent and utterances disassociated from the intent. The method may also include receiving live utterances. An intent may be determined for each live utterance. The method may include creating a vector representation of the live utterance. The method may include selecting candidate training utterances based on a comparison between the vector representation of the live utterance and the vector representation included in the binary classification model of the intent determined for the live utterance.
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公开(公告)号：US10943185B1
公开(公告)日：2021-03-09
申请号：US16167811
申请日：2018-10-23
Applicant: Bank of America Corporation
Inventor： David H. Witting , Maruthi Z Shanmugam , Jamaal C. Long , Matthew Hsieh , Luis Gerardo Mojica de la Vega , Viju Kothuvatiparambil , Mahalakshmi Chandra Sekaran , Donatus Asumu , Karen Trevino
IPC: G06N20/00 , G06F9/451 , G06F16/2457
Abstract: Aspects of the disclosure relate to supervised machine-learning (“ML”) training platforms for artificial intelligence (“AI”) computer systems. The ML training platform may include isolated update testing. The isolated update testing may feature a plurality of environments with various levels of isolation. The ML training platform may also include bi-directional channels for controlled update propagation.
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