公开(公告)号：US20240256963A1

公开(公告)日：2024-08-01

申请号：US18423774

申请日：2024-01-26

Applicant: Booz Allen Hamilton Inc.

Inventor： Edward Simon Paster Raff ,  Amol Ashish Khanna ,  Fred Sun Lu

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Exemplary systems and methods are directed to training a machine learning model and for preventing leakage of training data by the machine learning model subsequent to training. A processor is configured to convert a sparse dataset into a matrix of plural data coordinates, generate a priority queue populated with the plural data coordinates, and iteratively select a data coordinate from the priority queue. Plural model values are calculated such that any zero value in the sparse dataset is avoided while maintaining a same result. A next feature is selected, and its weight is altered. Plural variables of the matrix are updated based on the altered weight value, and the priority queue is updated to adjust a priority of the data coordinates based on the update to the plural variables. The process is repeated for each next data coordinate until the model converges to a solution based on the model weights.