公开(公告)号：US20210117786A1

公开(公告)日：2021-04-22

申请号：US17048023

申请日：2019-04-18

Applicant: DEEPMIND TECHNOLOGIES LIMITED

Inventor： Jonathan Schwarz ,  Razvan Pascanu ,  Raia Thais Hadsell ,  Wojciech Czarnecki ,  Yee Whye Teh ,  Jelena Luketina

IPC: G06N3/08 ,  G06N5/02 ,  G06N20/20 ,  G06K9/62

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scalable continual learning using neural networks. One of the methods includes receiving new training data for a new machine learning task; training an active subnetwork on the new training data to determine trained values of the active network parameters from initial values of the active network parameters while holding current values of the knowledge parameters fixed; and training a knowledge subnetwork on the new training data to determine updated values of the knowledge parameters from the current values of the knowledge parameters by training the knowledge subnetwork to generate knowledge outputs for the new training inputs that match active outputs generated by the trained active subnetwork for the new training inputs.

公开(公告)号：US20240394540A1

公开(公告)日：2024-11-28

申请号：US18674367

申请日：2024-05-24

Applicant: DEEPMIND TECHNOLOGIES LIMITED

Inventor： Jonathan Schwarz ,  Razvan Pascanu ,  Raia Thais Hadsell ,  Wojciech Czarnecki ,  Yee Whye Teh ,  Jelena Luketina

IPC: G06N3/084 ,  G06F18/22 ,  G06N3/08 ,  G06N5/02 ,  G06N20/20

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scalable continual learning using neural networks. One of the methods includes receiving new training data for a new machine learning task; training an active subnetwork on the new training data to determine trained values of the active network parameters from initial values of the active network parameters while holding current values of the knowledge parameters fixed; and training a knowledge subnetwork on the new training data to determine updated values of the knowledge parameters from the current values of the knowledge parameters by training the knowledge subnetwork to generate knowledge outputs for the new training inputs that match active outputs generated by the trained active subnetwork for the new training inputs.

公开(公告)号：US12020164B2

公开(公告)日：2024-06-25

申请号：US17048023

申请日：2019-04-18

Applicant: DEEPMIND TECHNOLOGIES LIMITED

Inventor： Jonathan Schwarz ,  Razvan Pascanu ,  Raia Thais Hadsell ,  Wojciech Czarnecki ,  Yee Whye Teh ,  Jelena Luketina

IPC: G06N3/08 ,  G06F18/22 ,  G06N3/084 ,  G06N5/02 ,  G06N20/20

CPC classification number: G06N3/084 ,  G06F18/22 ,  G06N3/08 ,  G06N5/02 ,  G06N20/20

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scalable continual learning using neural networks. One of the methods includes receiving new training data for a new machine learning task; training an active subnetwork on the new training data to determine trained values of the active network parameters from initial values of the active network parameters while holding current values of the knowledge parameters fixed; and training a knowledge subnetwork on the new training data to determine updated values of the knowledge parameters from the current values of the knowledge parameters by training the knowledge subnetwork to generate knowledge outputs for the new training inputs that match active outputs generated by the trained active subnetwork for the new training inputs.