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Tree-Based Convolutional Neural Netw...
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Tree-Based Convolutional Neural Networks = Principles and Applications /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Tree-Based Convolutional Neural Networks/ by Lili Mou, Zhi Jin.
其他題名:
Principles and Applications /
作者:
Mou, Lili.
其他作者:
Jin, Zhi.
面頁冊數:
XV, 96 p. 32 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Artificial intelligence. -
電子資源:
https://doi.org/10.1007/978-981-13-1870-2
ISBN:
9789811318702
Tree-Based Convolutional Neural Networks = Principles and Applications /
Mou, Lili.
Tree-Based Convolutional Neural Networks
Principles and Applications /[electronic resource] :by Lili Mou, Zhi Jin. - 1st ed. 2018. - XV, 96 p. 32 illus.online resource. - SpringerBriefs in Computer Science,2191-5768. - SpringerBriefs in Computer Science,.
Introduction -- Preliminaries and Related Work -- General Concepts of Tree-Based Convolutional Neural Networks (TBCNNs) -- TBCNN for Programs’ Abstract Syntax Trees (ASTs) -- TBCNN for Constituency Trees in Natural Language Processing -- TBCNN for Dependency Trees in Natural Language Processing -- Concluding Remarks.
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.
ISBN: 9789811318702
Standard No.: 10.1007/978-981-13-1870-2doiSubjects--Topical Terms:
559380
Artificial intelligence.
LC Class. No.: Q334-342
Dewey Class. No.: 006.3
Tree-Based Convolutional Neural Networks = Principles and Applications /
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