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:
Mar. 17, 2020

Filed:

Oct. 26, 2018
Applicant:

Capital One Services, Llc, McLean, VA (US);

Inventors:

Austin Walters, Savoy, IL (US);

Jeremy Goodsitt, Champaign, IL (US);

Anh Truong, Champaign, IL (US);

Fardin Abdi Taghi Abad, Champaign, IL (US);

Mark Watson, Urbana, IL (US);

Vincent Pham, Champaign, IL (US);

Kate Key, Effingham, IL (US);

Reza Farivar, Champaign, IL (US);

Noriaki Tatsumi, Silver Spring, MD (US);

Assignee:

Capital One Services, LLC, McLean, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 11/36 (2006.01); G06N 20/00 (2019.01); G06F 9/54 (2006.01); G06F 8/71 (2018.01); H04L 29/08 (2006.01); G06F 17/16 (2006.01); G06F 17/18 (2006.01); G06N 3/04 (2006.01); G06F 16/28 (2019.01); G06F 16/242 (2019.01); G06F 16/248 (2019.01); G06F 16/25 (2019.01); G06T 7/194 (2017.01); G06T 7/246 (2017.01); G06K 9/66 (2006.01); G06T 11/00 (2006.01); G06N 3/08 (2006.01); G06N 7/00 (2006.01); G06F 16/906 (2019.01); G06K 9/62 (2006.01); G06F 16/903 (2019.01); G06F 16/9038 (2019.01); G06F 16/9032 (2019.01); G06F 21/62 (2013.01); G06N 5/04 (2006.01); G06F 16/93 (2019.01); G06Q 10/04 (2012.01); G06F 17/15 (2006.01); G06F 16/2455 (2019.01); G06F 21/60 (2013.01); G06F 30/20 (2020.01); G06K 9/03 (2006.01); G06F 40/166 (2020.01); G06F 40/20 (2020.01); G06K 9/68 (2006.01); G06K 9/72 (2006.01); G06F 16/22 (2019.01); G06F 16/335 (2019.01); G06F 40/117 (2020.01); G06F 21/55 (2013.01); H04L 29/06 (2006.01); G06T 7/254 (2017.01); H04N 21/234 (2011.01); H04N 21/81 (2011.01);
U.S. Cl.
CPC ...
G06F 11/3608 (2013.01); G06F 8/71 (2013.01); G06F 9/54 (2013.01); G06F 9/541 (2013.01); G06F 9/547 (2013.01); G06F 11/3628 (2013.01); G06F 11/3636 (2013.01); G06F 16/2237 (2019.01); G06F 16/2264 (2019.01); G06F 16/248 (2019.01); G06F 16/2423 (2019.01); G06F 16/24568 (2019.01); G06F 16/254 (2019.01); G06F 16/258 (2019.01); G06F 16/283 (2019.01); G06F 16/285 (2019.01); G06F 16/288 (2019.01); G06F 16/335 (2019.01); G06F 16/906 (2019.01); G06F 16/9038 (2019.01); G06F 16/90332 (2019.01); G06F 16/90335 (2019.01); G06F 16/93 (2019.01); G06F 17/15 (2013.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06F 21/552 (2013.01); G06F 21/60 (2013.01); G06F 21/6245 (2013.01); G06F 21/6254 (2013.01); G06F 30/20 (2020.01); G06F 40/117 (2020.01); G06F 40/166 (2020.01); G06F 40/20 (2020.01); G06K 9/036 (2013.01); G06K 9/6215 (2013.01); G06K 9/6218 (2013.01); G06K 9/6231 (2013.01); G06K 9/6232 (2013.01); G06K 9/6253 (2013.01); G06K 9/6256 (2013.01); G06K 9/6257 (2013.01); G06K 9/6262 (2013.01); G06K 9/6265 (2013.01); G06K 9/6267 (2013.01); G06K 9/6269 (2013.01); G06K 9/6277 (2013.01); G06K 9/66 (2013.01); G06K 9/6885 (2013.01); G06K 9/72 (2013.01); G06N 3/04 (2013.01); G06N 3/0445 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 3/088 (2013.01); G06N 5/04 (2013.01); G06N 7/00 (2013.01); G06N 7/005 (2013.01); G06N 20/00 (2019.01); G06Q 10/04 (2013.01); G06T 7/194 (2017.01); G06T 7/246 (2017.01); G06T 7/248 (2017.01); G06T 7/254 (2017.01); G06T 11/001 (2013.01); H04L 63/1416 (2013.01); H04L 63/1491 (2013.01); H04L 67/306 (2013.01); H04L 67/34 (2013.01); H04N 21/23412 (2013.01); H04N 21/8153 (2013.01);
Abstract

Automated systems and methods for optimizing a model are disclosed. For example, in an embodiment, a method for optimizing a model may comprise receiving a data input that includes a desired outcome and an input dataset identifier. The method may include retrieving an input dataset based on the identifier and receiving an input model based on the desired outcome. The method may also comprise using a data synthesis model to create a synthetic dataset based on the input dataset and a similarity metric. The method may also comprise debugging the input model using synthetic dataset to create a debugged model. The method may also comprise selecting an actual dataset based on the input dataset and the desired outcome. In some aspects, the method may comprise optimizing the debugged model using the actual dataset and storing the optimized model.


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