Patent · US Active

Resource allocation optimization for multi-dimensional machine learning environments

US11620162B2 · kind B2 · utility

0Cited by

0References

20Claims

0Family size

Assignee

CAPITAL ONE SERVICES, LLC · US

Inventors

Xinyu Chen · Bellaire, US
Abhishek Shrivastava · Pune, IN
Boryana Manz · McLean, US
Yingbo Li · Woodbury, US
Katelyn Ge · Frisco, US
Jason Redd · McLean, US
Shubham Chitkara · McLean, US
Pothuraju Tallapaneni · McLean, US

Key dates

Filing date	May 24, 2021
Grant date	Apr 4, 2023
Priority date	—
Expiry date	Oct 2, 2041

Classification

Technology area (CPC G)Physics
CPC primaryG06F11/3433
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Some embodiments of the present application include obtaining first data from a data feed to be provided to a plurality of machine learning models and detecting a changepoint in the first data. In response to the changepoint being detected, a first machine learning model may be executed on the first data to obtain first output datasets. A first performance score for the first machine learning model may be computed based on the first output datasets. A second machine learning model may be caused to execute on the first data based on the first performance score satisfying a first condition.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.