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:
Aug. 29, 2023

Filed:

Sep. 07, 2022
Applicant:

Tripleblind, Inc., Kansas City, MO (US);

Inventors:

Gharib Gharibi, Overland Park, MO (US);

Greg Storm, Kansas City, MO (US);

Ravi Patel, Kansas City, MO (US);

Riddhiman Das, Parkville, MO (US);

Assignee:

TripleBlind, Inc., Kansas City, MO (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/00 (2019.01); H04L 9/40 (2022.01); G06N 3/082 (2023.01); H04L 9/00 (2022.01); G06F 17/16 (2006.01); G06Q 30/0601 (2023.01); G06N 3/04 (2023.01); G06Q 20/40 (2012.01); H04L 9/06 (2006.01); G06F 18/24 (2023.01); G06F 18/2113 (2023.01); G06N 3/098 (2023.01); G06N 3/048 (2023.01); G06F 16/13 (2019.01); G06F 21/62 (2013.01);
U.S. Cl.
CPC ...
H04L 63/0428 (2013.01); G06F 16/13 (2019.01); G06F 17/16 (2013.01); G06F 18/2113 (2023.01); G06F 18/24 (2023.01); G06F 21/6245 (2013.01); G06N 3/04 (2013.01); G06N 3/048 (2023.01); G06N 3/082 (2013.01); G06N 3/098 (2023.01); G06Q 20/401 (2013.01); G06Q 30/0623 (2013.01); H04L 9/008 (2013.01); H04L 9/0625 (2013.01); G06Q 2220/00 (2013.01); H04L 2209/46 (2013.01);
Abstract

A method of providing blind vertical learning includes creating, based on assembled data, a neural network having n bottom portions and a top portion and transmitting each bottom portion of then bottom portions to a client device. The training of the neural network includes accepting a, output from each bottom portion of the neural network, joining the plurality of outputs at a fusion layer, passing the fused outputs to the top portion of the neural network, carrying out a forward propagation step at the top portion of neural network, calculating a loss value after the forward propagation step, calculating a set of gradients of the loss value with respect to server-side model parameters and passing subsets of the set of gradients to a client device. After training, the method includes combining the trained bottom portion from each client device into a combined model.


Find Patent Forward Citations

Loading…