公开(公告)号：US11928577B2

公开(公告)日：2024-03-12

申请号：US16859815

申请日：2020-04-27

Applicant: Google LLC

Inventor： Alexander Krizhevsky ,  Ilya Sutskever ,  Geoffrey E. Hinton

IPC: G06N3/04 ,  G06F18/214 ,  G06N3/045 ,  G06N3/063 ,  G06N3/08 ,  G06T1/20 ,  G06V10/44

CPC classification number: G06N3/063 ,  G06F18/214 ,  G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06T1/20 ,  G06V10/454

Abstract: A parallel convolutional neural network is provided. The CNN is implemented by a plurality of convolutional neural networks each on a respective processing node. Each CNN has a plurality of layers. A subset of the layers are interconnected between processing nodes such that activations are fed forward across nodes. The remaining subset is not so interconnected.

公开(公告)号：US10540587B2

公开(公告)日：2020-01-21

申请号：US14684186

申请日：2015-04-10

Applicant: Google LLC

Inventor： Alexander Krizhevsky

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a convolutional neural network (CNN). The system includes a plurality of workers, wherein each worker is configured to maintain a respective replica of each of the convolutional layers of the CNN and a respective disjoint partition of each of the fully-connected layers of the CNN, wherein each replica of a convolutional layer includes all of the nodes in the convolutional layer, and wherein each disjoint partition of a fully-connected layer includes a portion of the nodes of the fully-connected layer.

公开(公告)号：US20240346298A1

公开(公告)日：2024-10-17

申请号：US18438368

申请日：2024-02-09

Applicant: Google LLC

Inventor： Alexander Krizhevsky ,  Ilya Sutskever ,  Geoffrey E. Hinton

IPC: G06N3/063 ,  G06F18/214 ,  G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06T1/20 ,  G06V10/44

CPC classification number: G06N3/063 ,  G06F18/214 ,  G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06T1/20 ,  G06V10/454

Abstract: A parallel convolutional neural network is provided. The CNN is implemented by a plurality of convolutional neural networks each on a respective processing node. Each CNN has a plurality of layers. A subset of the layers are interconnected between processing nodes such that activations are fed forward across nodes. The remaining subset is not so interconnected.

公开(公告)号：US20210224659A1

公开(公告)日：2021-07-22

申请号：US17227010

申请日：2021-04-09

Applicant: Google LLC

Inventor： Geoffrey E. Hinton ,  Alexander Krizhevsky ,  Ilya Sutskever ,  Nitish Srivastava

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/46

Abstract: A system for training a neural network. A switch is linked to feature detectors in at least some of the layers of the neural network. For each training case, the switch randomly selectively disables each of the feature detectors in accordance with a preconfigured probability. The weights from each training case are then normalized for applying the neural network to test data.

公开(公告)号：US20200327391A1

公开(公告)日：2020-10-15

申请号：US16859815

申请日：2020-04-27

Applicant: Google LLC

Inventor： Alexander Krizhevsky ,  Ilya Sutskever ,  Geoffrey E. Hinton

IPC: G06N3/04 ,  G06K9/66 ,  G06K9/62 ,  G06T1/20 ,  G06N3/063 ,  G06K9/46 ,  G06N3/08

Abstract: A parallel convolutional neural network is provided. The CNN is implemented by a plurality of convolutional neural networks each on a respective processing node. Each CNN has a plurality of layers. A subset of the layers are interconnected between processing nodes such that activations are fed forward across nodes. The remaining subset is not so interconnected.

公开(公告)号：US11829882B2

公开(公告)日：2023-11-28

申请号：US17227010

申请日：2021-04-09

Applicant: Google LLC

Inventor： Geoffrey E. Hinton ,  Alexander Krizhevsky ,  Ilya Sutskever ,  Nitish Srivastava

IPC: G06N3/082 ,  G06N3/045 ,  G06N3/047 ,  G06N3/084

CPC classification number: G06N3/082 ,  G06N3/045 ,  G06N3/047 ,  G06N3/084

Abstract: A system for training a neural network. A switch is linked to feature detectors in at least some of the layers of the neural network. For each training case, the switch randomly selectively disables each of the feature detectors in accordance with a preconfigured probability. The weights from each training case are then normalized for applying the neural network to test data.

公开(公告)号：US10977557B2

公开(公告)日：2021-04-13

申请号：US16523884

申请日：2019-07-26

Applicant: Google LLC

Inventor： Geoffrey E. Hinton ,  Alexander Krizhevsky ,  Ilya Sutskever ,  Nitish Srivastava

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/46

Abstract: A system for training a neural network. A switch is linked to feature detectors in at least some of the layers of the neural network. For each training case, the switch randomly selectively disables each of the feature detectors in accordance with a preconfigured probability. The weights from each training case are then normalized for applying the neural network to test data.

公开(公告)号：US10366329B2

公开(公告)日：2019-07-30

申请号：US15222870

申请日：2016-07-28

Applicant: Google LLC

Inventor： Geoffrey E. Hinton ,  Alexander Krizhevsky ,  Ilya Sutskever ,  Nitish Srivastava

IPC: G06N3/04 ,  G06N3/08 ,  G06K9/46

Abstract: A system for training a neural network. A switch is linked to feature detectors in at least some of the layers of the neural network. For each training case, the switch randomly selectively disables each of the feature detectors in accordance with a preconfigured probability. The weights from each training case are then normalized for applying the neural network to test data.