Invention Grant
- Patent Title: Regularizing machine learning models
-
Application No.: US15343458Application Date: 2016-11-04
-
Publication No.: US11531874B2Publication Date: 2022-12-20
- Inventor: Sergey Ioffe
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06K9/62 ; G06V10/44

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage medium, for training a neural network, wherein the neural network is configured to receive an input data item and to process the input data item to generate a respective score for each label in a predetermined set of multiple labels. The method includes actions of obtaining a set of training data that includes a plurality of training items, wherein each training item is associated with a respective label from the predetermined set of multiple labels; and modifying the training data to generate regularizing training data, comprising: for each training item, determining whether to modify the label associated with the training item, and changing the label associated with the training item to a different label from the predetermined set of labels, and training the neural network on the regularizing data.
Public/Granted literature
- US20170132512A1 REGULARIZING MACHINE LEARNING MODELS Public/Granted day:2017-05-11
Information query