公开(公告)号：US20170228642A1

公开(公告)日：2017-08-10

申请号：US15395553

申请日：2016-12-30

申请人： Google Inc.

发明人： Ivo Danihelka ,  Nal Emmerich Kalchbrenner ,  Gregory Duncan Wayne ,  Benigno Uría-Martínez ,  Alexander Benjamin Graves

IPC分类号： G06N3/08 ,  G06N3/04

CPC分类号： G06N3/08 ,  G06N3/04 ,  G06N3/0445

摘要： Systems, methods, and apparatus, including computer programs encoded on a computer storage medium, related to associative long short-term memory (LSTM) neural network layers configured to maintain N copies of an internal state for the associative LSTM layer, N being an integer greater than one. In one aspect, a system includes a recurrent neural network including an associative LSTM layer, wherein the associative LSTM layer is configured to, for each time step, receive a layer input, update each of the N copies of the internal state using the layer input for the time step and a layer output generated by the associative LSTM layer for a preceding time step, and generate a layer output for the time step using the N updated copies of the internal state.

公开(公告)号：US20170323201A1

公开(公告)日：2017-11-09

申请号：US15396331

申请日：2016-12-30

申请人： Google Inc.

发明人： Ilya Sutskever ,  Ivo Danihelka ,  Alexander Benjamin Graves ,  Gregory Duncan Wayne ,  Wojciech Zaremba

IPC分类号： G06N3/08 ,  G06F3/06

CPC分类号： G06N3/08 ,  G06F3/0604 ,  G06F3/0653 ,  G06F3/0673 ,  G06N3/0445 ,  G06N3/063

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks with an external memory using reinforcement learning. One of the methods includes providing an output derived from the system output portion of the neural network output as a system output in the sequence of system outputs; selecting a memory access process from a predetermined set of memory access processes for accessing the external memory from the reinforcement learning portion of the neural network output; writing and reading data from locations in the external memory in accordance with the selected memory access process using the differentiable portion of the neural network output; and combining the data read from the external memory with a next system input in the sequence of system inputs to generate a next neural network input in the sequence of neural network inputs.

公开(公告)号：US20170228638A1

公开(公告)日：2017-08-10

申请号：US15424685

申请日：2017-02-03

申请人： Google Inc.

发明人： Ivo Danihelka ,  Gregory Duncan Wayne ,  Fu-min Wang ,  Edward Thomas Grefenstette ,  Jack William Rae ,  Alexander Benjamin Graves ,  Timothy Paul Lillicrap ,  Timothy James Alexander Harley ,  Jonathan James Hunt

IPC分类号： G06N3/063 ,  G06N3/04 ,  G06N3/08

CPC分类号： G06N3/063 ,  G06N3/0445 ,  G06N3/082

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks with an external memory. One of the systems includes a sparse memory access subsystem that is configured to perform operations comprising generating a sparse set of reading weights that includes a respective reading weight for each of the plurality of locations in the external memory using the read key, reading data from the plurality of locations in the external memory in accordance with the sparse set of reading weights, generating a set of writing weights that includes a respective writing weight for each of the plurality of locations in the external memory, and writing the write vector to the plurality of locations in the external memory in accordance with the writing weights.

公开(公告)号：US20170169332A1

公开(公告)日：2017-06-15

申请号：US15374974

申请日：2016-12-09

申请人： Google Inc.

发明人： Alexander Benjamin Graves ,  Ivo Danihelka ,  Timothy James Alexander Harley ,  Malcolm Kevin Campbell Reynolds ,  Gregory Duncan Wayne

IPC分类号： G06N3/08 ,  G06N3/04

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks with an external memory. One of the systems includes a memory interface subsystem that is configured to perform operations comprising determining a respective content-based weight for each of a plurality of locations in an external memory; determining a respective allocation weight for each of the plurality of locations in the external memory; determining a respective final writing weight for each of the plurality of locations in the external memory from the respective content-based weight for the location and the respective allocation weight for the location; and writing data defined by the write vector to the external memory in accordance with the final writing weights.

公开(公告)号：US20160189027A1

公开(公告)日：2016-06-30

申请号：US14977201

申请日：2015-12-21

申请人： Google Inc.

发明人： Alexander Benjamin Graves ,  Ivo Danihelka ,  Gregory Duncan Wayne

IPC分类号： G06N3/08 ,  G06N3/063

CPC分类号： G06N3/08 ,  G06N3/0454 ,  G06N3/063

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks to generate additional outputs. One of the systems includes a neural network and a sequence processing subsystem, wherein the sequence processing subsystem is configured to perform operations comprising, for each of the system inputs in a sequence of system inputs: receiving the system input; generating an initial neural network input from the system input; causing the neural network to process the initial neural network input to generate an initial neural network output for the system input; and determining, from a first portion of the initial neural network output for the system input, whether or not to cause the neural network to generate one or more additional neural network outputs for the system input.

摘要翻译： 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，用于增加神经网络以产生附加输出。 系统中的一个包括神经网络和序列处理子系统，其中序列处理子系统被配置为对系统输入中的每一个执行包括系统输入序列的操作：接收系统输入; 从系统输入产生初始神经网络输入; 使神经网络处理初始神经网络输入，为系统输入生成初始神经网络输出; 以及从所述系统输入的所述初始神经网络输出的第一部分确定是否使所述神经网络生成用于所述系统输入的一个或多个附加神经网络输出。

公开(公告)号：US20160117586A1

公开(公告)日：2016-04-28

申请号：US14885086

申请日：2015-10-16

申请人： Google Inc.

发明人： Alexander Benjamin Graves ,  Ivo Danihelka ,  Gregory Duncan Wayne

IPC分类号： G06N3/04 ,  G06N3/08

CPC分类号： G06N3/04 ,  G06N3/08

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks with an external memory. One of the methods includes providing an output derived from a first portion of a neural network output as a system output; determining one or more sets of writing weights for each of a plurality of locations in an external memory; writing data defined by a third portion of the neural network output to the external memory in accordance with the sets of writing weights; determining one or more sets of reading weights for each of the plurality of locations in the external memory from a fourth portion of the neural network output; reading data from the external memory in accordance with the sets of reading weights; and combining the data read from the external memory with a next system input to generate the next neural network input.

摘要翻译： 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，用于利用外部存储器增强神经网络。 一种方法包括提供从神经网络输出的第一部分导出的输出作为系统输出; 为外部存储器中的多个位置中的每一个确定一组或多组写入权重; 根据所述书写权重集将所述神经网络输出的第三部分定义的数据写入所述外部存储器; 从所述神经网络输出的第四部分确定所述外部存储器中的所述多个位置中的每一个的一组或多组读取权重; 根据阅读权重集从外部存储器读取数据; 以及将从外部存储器读取的数据与下一个系统输入组合以生成下一个神经网络输入。

公开(公告)号：US20170140270A1

公开(公告)日：2017-05-18

申请号：US15349950

申请日：2016-11-11

申请人： Google Inc.

发明人： Volodymyr Mnih ,  Adrià Puigdomènech Badia ,  Alexander Benjamin Graves ,  Timothy James Alexander Harley ,  David Silver ,  Koray Kavukcuoglu

IPC分类号： G06N3/08 ,  G06N3/04

CPC分类号： G06N3/08 ,  G06N3/04 ,  G06N3/0454

摘要： Methods, systems, and apparatus, including computer programs encoded on computer storage media, for asynchronous deep reinforcement learning. One of the systems includes a plurality of workers, wherein each worker is configured to operate independently of each other worker, and wherein each worker is associated with a respective actor that interacts with a respective replica of the environment during the training of the deep neural network.