Invention Grant
- Patent Title: Automated input-data monitoring to dynamically adapt machine-learning techniques
-
Application No.: US16875825Application Date: 2020-05-15
-
Publication No.: US11562297B2Publication Date: 2023-01-24
- Inventor: Moises Goldszmidt , Anatoly D. Adamov , Juan C. Garcia , Julia R. Reisler , Timothy S. Paek , Vishwas Kulkarni , Yu-Chung Hsiao , Pavan Chitta
- Applicant: Apple Inc.
- Applicant Address: US CA Cupertino
- Assignee: Apple Inc.
- Current Assignee: Apple Inc.
- Current Assignee Address: US CA Cupertino
- Agency: Kilpatrick Townsend & Stockton LLP
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06K9/62

Abstract:
Systems and methods are disclosed for triggering an update to a machine-learning model upon detecting that a distribution of particular (e.g., recently collected) input data set is sufficiently different from a distribution training input data set used to train the model. The distributions may be determined to be sufficiently different when a classifier can identify to which distribution individual data elements belong (e.g., to at least a predetermined degree). An update to the machine-learning model can include morphing weights used by the model and/or retraining the model.
Public/Granted literature
- US20210224687A1 AUTOMATED INPUT-DATA MONITORING TO DYNAMICALLY ADAPT MACHINE-LEARNING TECHNIQUES Public/Granted day:2021-07-22
Information query