公开(公告)号：US20250053801A1

公开(公告)日：2025-02-13

申请号：US18447003

申请日：2023-08-09

Applicant: Microsoft Technology Licensing, LLC

Inventor： Xiaojing Chen ,  Jiong Zhang ,  Sen Zhou ,  Zhenjie Zhang

IPC: G06N3/08

Abstract: Embodiments of the disclosed technologies are capable of providing a ranking of digital content using a machine learning model. The machine learning model is configured for multi-task learning for dependent multi-objective optimization. Embodiments configure a memory according to a machine learning model, where the machine learning model includes a shared backbone and multiple heads. Each of the multiple heads are trained to perform a task associated with a first objective of a second objective.

公开(公告)号：US11792167B2

公开(公告)日：2023-10-17

申请号：US17219482

申请日：2021-03-31

Applicant: Microsoft Technology Licensing, LLC

Inventor： Haifeng Zhao ,  Yang Chen ,  Jiashuo Wang ,  Xiaojing Chen ,  Chencheng Wu ,  Souvik Ghosh ,  Ankit Gupta ,  Jing Wang ,  John Patrick Moore ,  Henry Heyburn Pistell ,  Mira Thambireddy ,  Haowen Cao ,  Keyi Yu

IPC: H04L9/40 ,  G06N20/00

CPC classification number: H04L63/0428 ,  G06N20/00

Abstract: Techniques for a flexible data security and machine learning system for merging third-party data are provided. In one technique, the system receives a data set from a third-party entity and receives selection data that indicates that the third-party entity selected a set of data security policies that includes an encryption option and a data mixing option from among multiple data mixing options. In response to receiving the selection data, the system stores data that associates the set of data security policies with the data set, encrypts the data set according to the encryption option, and persistently stores the encrypted data set. Later, the system decrypts the encrypted data set in volatile memory, generates, based on the data mixing option, training data based on the decrypted version of the data set, trains a machine-learned model based on the training data, and stores the machine-learned model in association with the data set.