公开(公告)号：US20160358073A1

公开(公告)日：2016-12-08

申请号：US15174020

申请日：2016-06-06

Applicant: Google Inc.

Inventor： Guillaume Desjardins ,  Karen Simonyan ,  Koray Kavukcuoglu ,  Razvan Pascanu

IPC: G06N3/08 ,  G06N99/00 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/04 ,  G06N3/084 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using a neural network system that includes a whitened neural network layer. One of the methods includes receiving an input activation generated by a layer before the whitened neural network layer in the sequence; processing the received activation in accordance with a set of whitening parameters to generate a whitened activation; processing the whitened activation in accordance with a set of layer parameters to generate an output activation; and providing the output activation as input to a neural network layer after the whitened neural network layer in the sequence.

Abstract translation: 方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于使用包含白化神经网络层的神经网络系统处理输入。 其中一种方法包括在序列中接收由白化神经网络层之前的层产生的输入激活; 根据一组增白参数来处理接收到的激活以产生白化激活; 根据一组层参数处理白化激活以产生输出激活; 并且在序列中的白化神经网络层之后，将输出激活提供给神经网络层的输入。

公开(公告)号：US20170337464A1

公开(公告)日：2017-11-23

申请号：US15396319

申请日：2016-12-30

Applicant: Google Inc.

Inventor： Neil Charles Rabinowitz ,  Guillaume Desjardins ,  Andrei-Alexandru Rusu ,  Koray Kavukcuoglu ,  Raia Thais Hadsell ,  Razvan Pascanu ,  James Kirkpatrick ,  Hubert Josef Soyer

IPC: G06N3/04 ,  G06N3/08 ,  G06F17/16

CPC classification number: G06F17/16 ,  G06N3/0454

Abstract: Methods and systems for performing a sequence of machine learning tasks. One system includes a sequence of deep neural networks (DNNs), including: a first DNN corresponding to a first machine learning task, wherein the first DNN comprises a first plurality of indexed layers, and each layer in the first plurality of indexed layers is configured to receive a respective layer input and process the layer input to generate a respective layer output; and one or more subsequent DNNs corresponding to one or more respective machine learning tasks, wherein each subsequent DNN comprises a respective plurality of indexed layers, and each layer in a respective plurality of indexed layers with index greater than one receives input from a preceding layer of the respective subsequent DNN, and one or more preceding layers of respective preceding DNNs, wherein a preceding layer is a layer whose index is one less than the current index.