GCAE_ATT (Gated Convolutional Networks Aspcet Embedding with attention) 此网络基本符合原有网络架构,但是在网络第一步:在句子glove向量和CNN之间加了一层Scaled Dot-Product Attention,其作用是更好的表达了句子的特征,提取出更多的信息,其代码如下: def gate_cnn_model_att(sentence,aspect,kernel_num,kernel_si...
题目:Language Modeling with Gated Convolutional Networks 原文链接:arxiv.org/pdf/1612.0808 参考代码:anantzoid/Language-Modeling-GatedCNN 之前语言模型的主流方法都是基于RNN,本篇论文提出了一种新颖的门控机制,结合CNN网络应用到语言模型。该网络包含多层,与经典语法形式相似,能分层次地分析输入,构建了增加粒度的...
中山大学的团队提出了一种 Gated Convolutional Networks 用于处理这样的问题，模型主要包括输入层、卷积层和输出层。其中的核心是卷积层用到的 Gated Convolution (门卷积)。由于 SemEval-2018 任务可以使用外部信息，例如一些常识知识，因此作者也利用 ConceptNet (一个多语言常识知识图谱) 获取单词之间的关系，并学习关...
模型的结构图如下所示: 首先我们可以通过堆叠CNN来标识长文本,提取更高层、更抽象的特征,而且相比LSTM而言,我们需要的op更少(CNN需要O(N/k)个op,而LSTM将文本视为序列需要O(N)个op,其中N为文本长度,k为卷积核宽度),这样一来,我们需要的非线性操作也更少,有效地降低了梯度弥散的现象,使模型收敛和训练变得更加...
In this paper, we study the problem of commonsense machine comprehension and propose a new model based on convolutional neural networks and Gated Tanh-ReLU Units. The new model, which serves as an alternative to exiting recurrent models, consists of three layers: input layer, gated convolutional ...
Language Modeling with Gated Convolutional Networks 语言模型 所谓的语言模型,即是指在得知前面的若干个单词的时候,下一个位置上出现的某个单词的概率。 最朴素的方法是N-gram语言模型,即当前位置只和前面N个位置的单词相关。如此,问题便是,N小了,语言模型的表达能力不够。N大了,遇到稀疏性问题,无法有效的表征...
Language Modeling with Gated Convolutional Networks Yann N. Dauphin Angela Fan Michael Auli David Grangier Facebook AI Research 6 1 0 Abstract bedding words in continuous space over which a neural net- 2 work is applied. The current state of the art to language The pre-dominant approach to ...
3.2. Gated convolutional neural networks A GCNN is a non-recurrent network alternative to capture long-term dependencies while avoiding sequential operations for better parallelizability. Thus, recurrent connections typically applied in RNNs are replaced by gated temporal convolutions. In general, convol...
Gated Convolutional Neural Networks with Sentence-Related Selection for Distantly Supervised Relation Extraction SUMMARY Relation extraction is one of the key basic tasks in natural language processing in which distant supervision is widely used for obtaining large-sc... Y Chen,S Li,X Li,... - 《...
This can be addressed well by Convolutional Neural Networks (CNN) which supports automatic feature extraction. It is capable of learning the global features from images effectively for image classification. But it loses the context of local information among the pixels that need to be retained for ...