PRIVACY PRESERVING CROSS-DOMAIN MACHINE LEARNING

PRIVACY PRESERVING CROSS-DOMAIN MACHINE LEARNING

This document describes a secure machine learning platform. In some aspects, a method includes transmitting by the application to the machine learning platform, a set of data including a user profile, one or more characteristics of a digital component, contextual signals, model identifier, and data...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Wang, Gang, Bai, Yijian
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This document describes a secure machine learning platform. In some aspects, a method includes transmitting by the application to the machine learning platform, a set of data including a user profile, one or more characteristics of a digital component, contextual signals, model identifier, and data indicating a type of event. The application receives a request generated based on the computer-readable instructions to upload a user profile of a user of the client device to a machine learning platform. The computer-readable instructions initiate the request in response to detecting an occurrence of the event with the digital component. In response to the request, the application can obtain the user profile request data element that includes a model identifier for a machine learning model and one or more characteristics of at least one of the digital component or the first content page.