Tree-Based Convolutional Neural Networks Principles and Applications

This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data. TBCNNsare related to existing convolutional neural networks (CNNs) and recursive neural networks (RNNs), but they combine the merits of both: thanks to their short p...

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Bibliographic Details
Main Authors: Mou, Lili, Jin, Zhi (Author)
Format: eBook
Language:English
Published: Singapore Springer Nature Singapore 2018, 2018
Edition:1st ed. 2018
Series:SpringerBriefs in Computer Science
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary:This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data. TBCNNsare related to existing convolutional neural networks (CNNs) and recursive neural networks (RNNs), but they combine the merits of both: thanks to their short propagation path, they are as efficient in learning as CNNs; yet they are also as structure-sensitive as RNNs. In this book, readers will also find a comprehensive literature review of related work, detailed descriptions of TBCNNs and their variants, and experiments applied to program analysis and natural language processing tasks. It is also an enjoyable read for all those with a general interest in deep learning
Physical Description:XV, 96 p. 32 illus online resource
ISBN:9789811318702