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UTILISATION DE REPRÉSENTATIONS HIÉRARCHIQUES POUR UNE RECHERCHE D'ARCHITECTURE DE RÉSEAU NEURONAL

摘要

A computer-implemented method for automatically determining a neural network architecture represents a neural network architecture as a data structure defining a hierarchical set of directed acyclic graphs in multiple levels. Each graph has an input, an output, and a plurality of nodes between the input and the output. At each level, a corresponding set of the nodes are connected pairwise by directed edges which indicate operations performed on outputs of one node to generate an input to another node. Each level is associated with a corresponding set of operations. At a lowest level, the operations associated with each edge are selected from a set of primitive operations. The method includes repeatedly generating new sample neural network architectures, and evaluating their fitness. The modification is performed by selecting a level, selecting two nodes at that level, and modifying, removing or adding an edge between those nodes according to operations associated with lower levels of the hierarchy.

著录项

  • 公开/公告号EP3676765A1

    专利类型

  • 公开/公告日2020.07.08

    原文格式PDF

  • 申请/专利权人

    申请/专利号EP18793416.1

  • 发明设计人

    申请日2018.10.26

  • 分类号

  • 国家 EP

  • 入库时间 2022-08-21 10:52:54

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