BR112017003893A8 - Rede dnn aluno aprendiz via distribuição de saída - Google Patents

Rede dnn aluno aprendiz via distribuição de saída

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Publication number
BR112017003893A8
BR112017003893A8 BR112017003893A BR112017003893A BR112017003893A8 BR 112017003893 A8 BR112017003893 A8 BR 112017003893A8 BR 112017003893 A BR112017003893 A BR 112017003893A BR 112017003893 A BR112017003893 A BR 112017003893A BR 112017003893 A8 BR112017003893 A8 BR 112017003893A8
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dnn network
student
dnn
network model
teacher
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BR112017003893A
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BR112017003893A2 (pt
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Zhao Rui
Huang Jui-Ting
Li Jinyu
Gong Yifan
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Microsoft Corp
Microsoft Technology Licensing Llc
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/082Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/084Backpropagation, e.g. using gradient descent
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computing arrangements based on specific mathematical models
    • G06N7/01Probabilistic graphical models, e.g. probabilistic networks
    • GPHYSICS
    • G09EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09BEDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B5/00Electrically-operated educational appliances

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  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Image Analysis (AREA)
  • Machine Translation (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Electrically Operated Instructional Devices (AREA)

Abstract

MÉTODO PARA GERAR UM MODELO DE REDE DNN TREINADA PARA INSTALAÇÃO COMO UM CLASSIFICADOR EM UM SISTEMA DE COMPUTADOR, MEIO LEGÍVEL POR COMPUTADOR E CLASSIFICADOR DE REDE DNN. A presente invenção refere-se a sistemas e métodos para a geração de um classificador de rede DNN por meio do "aprendizado" de um modelo de rede DNN "aluno" a partir de um modelo de rede DNN "professor" mais preciso e maior. A rede DNN aluno pode ser treinada a partir de dados de treinamento não rotulados ao passar os dados de treinamento não rotulados pela rede DNN professor, a qual poderá ser treinada a partir de dados rotulados. Em uma modalidade, um processo iterativo é aplicado no sentido de treinar a rede DNN aluno ao minimizar a divergência das distribuições de saída dos modelos de redes DNN professor e aluno. Para cada iteração até a convergência, a diferença nas saídas dessas duas redes DNN é usada no sentido de atualizar o modelo de rede DNN aluno, e saídas são determinadas novamente, usando os dados de treinamento não rotulados. O modelo de rede DNN aluno treinado resultante poderá ser adequado para a provisão de aplicações de processamento de sinal precisas em dispositivos que tenham limitados recursos em termos de computação ou de armazenamento, tais como dispositivos móveis ou vestíveis. Em uma modalidade, o modelo de rede DNN professor compreende modelos de conjuntos de redes DNN.
BR112017003893A 2014-09-12 2014-09-12 Rede dnn aluno aprendiz via distribuição de saída BR112017003893A8 (pt)

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PCT/CN2014/086397 WO2016037350A1 (en) 2014-09-12 2014-09-12 Learning student dnn via output distribution

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BR112017003893A2 BR112017003893A2 (pt) 2017-12-05
BR112017003893A8 true BR112017003893A8 (pt) 2017-12-26

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US (1) US11429860B2 (pt)
EP (1) EP3192012A4 (pt)
JP (1) JP6612855B2 (pt)
CN (1) CN106170800A (pt)
BR (1) BR112017003893A8 (pt)
RU (1) RU2666631C2 (pt)
WO (1) WO2016037350A1 (pt)

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BR112017003893A2 (pt) 2017-12-05
RU2666631C2 (ru) 2018-09-11
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