公开(公告)号：US20230137905A1

公开(公告)日：2023-05-04

申请号：US18089513

申请日：2022-12-27

Applicant: Intel Corporation

Inventor： Amrutha Machireddy ,  Ranganath Krishnan ,  Nilesh Ahuja ,  Omesh Tickoo

IPC: G06N3/091

Abstract: Disclosed is an example solution to perform source-free active adaptation to distributional shifts for machine learning. The example solution includes: interface circuitry; programmable circuitry; and instructions to cause the programmable circuitry to: perform a first training of a neural network on a baseline data set associated with a first data distribution; compare data of a shifted data set to a threshold uncertainty value, wherein the threshold uncertainty value is associated with a distributional shift between the baseline data set and the shifted data set; generate a shifted data subset including items of the shifted dataset that satisfy the threshold uncertainty value; and perform a second training of the neural network based on the shifted data subset.