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:
Jul. 28, 2020

Filed:

Sep. 27, 2018
Applicant:

Leapyear Technologies, Inc., Berkeley, CA (US);

Inventors:

Ishaan Nerurkar, Berkeley, CA (US);

Christopher Hockenbrocht, Berkeley, CA (US);

Liam Damewood, Walnut Creek, CA (US);

Mihai Maruseac, Berkeley, CA (US);

Alexander Rozenshteyn, Berkeley, CA (US);

Assignee:

LeapYear Technologies, Inc., Berkeley, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 21/62 (2013.01); G06K 9/62 (2006.01); G16H 10/60 (2018.01); G06N 20/00 (2019.01); G06F 17/18 (2006.01); G06F 16/2455 (2019.01); G06F 16/248 (2019.01); G06N 20/20 (2019.01); G06N 5/00 (2006.01); G06F 17/11 (2006.01); G06N 20/10 (2019.01);
U.S. Cl.
CPC ...
G06F 21/6245 (2013.01); G06F 16/248 (2019.01); G06F 16/2455 (2019.01); G06F 17/18 (2013.01); G06F 21/6254 (2013.01); G06K 9/6282 (2013.01); G06N 5/003 (2013.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G16H 10/60 (2018.01); G06F 17/11 (2013.01); G06F 2221/2145 (2013.01); G06K 9/6256 (2013.01); G06N 20/10 (2019.01);
Abstract

A request from a client is received to generate a differentially private random forest classifier trained using a set of restricted data. The differentially private random forest classifier is generated in response to the request. Generating the differentially private random forest classifier includes determining a number of decision trees and generating the determined number of decision trees. Generating a decision tree includes generating a set of splits based on the restricted data, determining an information gain for each split, selecting a split from the set using an exponential mechanism, and adding the split to the decision tree. The differentially private random forest classifier is provided to the client.


Find Patent Forward Citations

Nerurkar, Ishaan. (2020). Differentially private machine learning using a random forest classifier (U.S. Patent No. 10726153). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/10726153

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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