公开(公告)号：US11526755B2

公开(公告)日：2022-12-13

申请号：US16882332

申请日：2020-05-22

Applicant: DeepMind Technologies Limited

Inventor： Chongli Qin ,  Sven Adrian Gowal ,  Soham De ,  Robert Stanforth ,  James Martens ,  Krishnamurthy Dvijotham ,  Dilip Krishnan ,  Alhussein Fawzi

IPC: G06N3/08 ,  G06K9/62 ,  G06V10/82

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. One of the methods includes processing each training input using the neural network and in accordance with the current values of the network parameters to generate a network output for the training input; computing a respective loss for each of the training inputs by evaluating a loss function; identifying, from a plurality of possible perturbations, a maximally non-linear perturbation; and determining an update to the current values of the parameters of the neural network by performing an iteration of a neural network training procedure to decrease the respective losses for the training inputs and to decrease the non-linearity of the loss function for the identified maximally non-linear perturbation.

公开(公告)号：US20230252286A1

公开(公告)日：2023-08-10

申请号：US18079791

申请日：2022-12-12

Applicant: DeepMind Technologies Limited

Inventor： Chongli Qin ,  Sven Adrian Gowal ,  Soham De ,  Robert Stanforth ,  James Martens ,  Krishnamurthy Dvijotham ,  Dilip Krishnan ,  Alhussein Fawzi

IPC: G06N3/08 ,  G06V10/82 ,  G06F18/214 ,  G06F18/2135 ,  G06V10/764 ,  G06V10/774

CPC classification number: G06N3/08 ,  G06V10/82 ,  G06F18/214 ,  G06F18/21355 ,  G06V10/764 ,  G06V10/774

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. One of the methods includes processing each training input using the neural network and in accordance with the current values of the network parameters to generate a network output for the training input; computing a respective loss for each of the training inputs by evaluating a loss function; identifying, from a plurality of possible perturbations, a maximally non-linear perturbation; and determining an update to the current values of the parameters of the neural network by performing an iteration of a neural network training procedure to decrease the respective losses for the training inputs and to decrease the non-linearity of the loss function for the identified maximally non-linear perturbation.

公开(公告)号：US11775830B2

公开(公告)日：2023-10-03

申请号：US18079791

申请日：2022-12-12

Applicant: DeepMind Technologies Limited

Inventor： Chongli Qin ,  Sven Adrian Gowal ,  Soham De ,  Robert Stanforth ,  James Martens ,  Krishnamurthy Dvijotham ,  Dilip Krishnan ,  Alhussein Fawzi

IPC: G06N3/08 ,  G06V10/82 ,  G06F18/214 ,  G06F18/2135 ,  G06V10/764 ,  G06V10/774

CPC classification number: G06N3/08 ,  G06F18/214 ,  G06F18/21355 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. One of the methods includes processing each training input using the neural network and in accordance with the current values of the network parameters to generate a network output for the training input; computing a respective loss for each of the training inputs by evaluating a loss function; identifying, from a plurality of possible perturbations, a maximally non-linear perturbation; and determining an update to the current values of the parameters of the neural network by performing an iteration of a neural network training procedure to decrease the respective losses for the training inputs and to decrease the non-linearity of the loss function for the identified maximally non-linear perturbation.