[PDF] Top 20 Discriminative Neural Sentence Modeling by Tree Based Convolution
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Discriminative Neural Sentence Modeling by Tree Based Convolution
... a tree has maximum depth d, we pool nodes of less than α · d lay- ers to a TOP slot (α is set to ...constituency tree, it is not completely obvious how to pool features to more than 3 slots and comply with ... See full document
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Convolutional Neural Networks vs Convolution Kernels: Feature Engineering for Answer Sentence Reranking
... effectively modeling Q and AP pairs generating relational features we initially mod- eled in (Severyn and Moschitti, 2015; Severyn and Moschitti, ...two sentence models based on ... See full document
11
ABCNN: Attention Based Convolutional Neural Network for Modeling Sentence Pairs
... without taking the entire sentence contexts into ac- count. This observation was also investigated by Yao et al. (2013b) where an information retrieval system retrieves sentences with tokens labeled as DATE by ... See full document
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Sentence Modeling with Gated Recursive Neural Network
... MaxTDNN sentence model is based on the architecture of the Time-Delay Neural Network (TDNN) (Waibel et ...lutional neural network (DCNN) (Kalchbrenner et ...RecNN based models. ... See full document
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Multichannel Variable Size Convolution for Sentence Classification
... In recent years, deep learning models have achieved remarkable results in computer vision (Krizhevsky et al., 2012), speech recognition (Graves et al., 2013) and NLP (Collobert and We- ston, 2008). A problem largely ... See full document
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Natural Language Inference by Tree Based Convolution and Heuristic Matching
... convolutional neural networks (CNNs) as the individual sentence model, where a set of feature detectors over successive words are designed to extract local ...recurrent neural networks (RNNs) to ... See full document
7
Enhancing Unsupervised Generative Dependency Parser with Contextual Information
... are based on probabilistic generative models that learn the joint distribution of the given sentence and its ...dependency tree into factorized gram- mar rules, which lack the global features of the ... See full document
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Convolution Enhanced Bilingual Recursive Neural Network for Bilingual Semantic Modeling
... (binary tree structure) of a bilingual ...improve tree con- struction by incorporating word alignments into their objective ...build tree structures of phrases according to the minimum reconstruction ... See full document
11
A Grammar-Based Structural CNN Decoder for Code Generation
... recurrent neural network (RNN) as the de- ...language sentence, and thus it may be inappropriate for RNN to capture such a long ...tional neural network (CNN) for code ...the tree-based ... See full document
8
Multi Perspective Sentence Similarity Modeling with Convolutional Neural Networks
... a tree-based LSTM neural network architecture for sentence model- ...convolutional neural network architec- ture for paraphrase identification, which we com- pare to in our ... See full document
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On Tree Based Neural Sentence Modeling
... with tree-based sentence en- coders have shown better results on many downstream ...existing tree-based encoders adopt syntactic parsing trees as the explicit structure ...different ... See full document
11
Image Description Using Deep Neural Network
... a sentence you have to know which words came before ...a sentence of 5 words, the network would be unrolled into a 5-layer neural network, one layer for each ... See full document
6
A Generative Parser with a Discriminative Recognition Algorithm
... language modeling (Collins, 1999; Henderson, 2003; Titov and Henderson, 2007; Petrov and Klein, 2007; Dyer et ...parse tree and the sentence—an objective that only indirectly relates to the goal of ... See full document
7
Vehicle Recognition based on Deep Convolution Neural Networks
... the convolution layer is to extract the local features and perform convolution operation for each position of the input image with multiple ...of convolution constitutes the feature maps c of the ... See full document
7
Convolution based neural attention with applications to sentiment classification
... including neural machine translation [19], text summarization [30] and text inference ...of neural attention is to learn an alignment of a source sequence and a target sequence (sequence-to-sequence tasks) ... See full document
11
Discriminative Sentence Compression with Soft Syntactic Evidence
... decision tree model of Knight and Marcu (2000) and our ...decision tree model of Knight and Marcu instead of the noisy-channel model since both performed nearly as well in their evaluation, and the ... See full document
8
Machine Learning Perspectives for Dental Imaging
... In recent years, the digital atlases of human anatomy have become more attention and also reviewed a lot in the area of medical image analysis research and also much effort has been put in developing medical imaging ... See full document
5
A Monolingual Tree based Translation Model for Sentence Simplification
... tical sentence to SW, thus the BLUE and NIST scores of Moses is the ...complex sentence by dropping, splitting and substitution, which results in two sentences that are quite different from the SW ... See full document
9
Graph convolutional networks: a comprehensive review
... Despite some successes of these embedding methods, many of them suffer from the limitations of the shallow learning mechanisms [11, 12] and might fail to discover the more complex patterns behind the graphs. Deep ... See full document
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