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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.
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