Using hierarchical representations for neural network architecture searching

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 i...

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Hauptverfasser: VINYALS ORIOL, LIU HANXIAO, KAVUKCUOGLU KORAY, SIMONYAN KAREN, FERNANDO CHRISANTHA THOMAS
Format: Patent
Sprache:chi ; eng
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Zusammenfassung: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 pair-wise 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 ofthe hierarchy. 一种用于自动确定神经