文件名称：自然语言处理.zip
文件大小：7.46MB
文件格式：ZIP
更新时间：2020-03-14 13:16:26
深度学习
应用于神经网络机器翻译的无显式分割字符级解码器 A character-level decoder without explicit segmentation for neural machine translation (2016) 作者J. Chung et al. 探索语言建模的局限性 Exploring the limits of language modeling (2016) 作者R. Jozefowicz et al. 教机器阅读和理解 Teaching machines to read and comprehend (2015) 作者 K. Hermann et al. 摘要：教机器阅读自然语言文档仍然是一个难以应付的挑战。对于看到的文档内容，我们可以测试机器阅读系统回答相关问题的能力，但是到目前为止，对于这种类型的评估仍缺少大规模的训练和测试数据集。在这项工作中，我们定义了一种新的方法来解决这个瓶颈，并提供了大规模的监督阅读理解数据。 这允许我们开发一类基于attention的深层神经网络，凭借最少的语言结构的先验知识来学习阅读真实文档和回答复杂的问题 。 attended-based神经网络机器翻译有效策略 Effective approaches to attention-based neural machine translation (2015) 作者 M. Luong et al. 通过共同学习对齐和翻译实现神经机器翻译 Neural machine translation by jointly learning to align and translate (2014) 作者 D. Bahdanau et al. 利用神经网络进行序列到序列的学习 Sequence to sequence learning with neural networks (2014) 作者I. Sutskever et al. 用 RNN 编码——解码器学习短语表征，实现统计机器翻译 Learning phrase representations using RNN encoder-decoder for statistical machine translation (2014) 作者K. Cho et al. 一个为句子建模的卷积神经网络 A convolutional neural network for modelling sentences (2014) 作者 N. Kalchbrenner et al. 用于句子分类的卷积神经网络 Convolutional neural networks for sentence classification (2014) 作者Y. Kim Glove: 用于词表征的全局向量 Glove: Global vectors for word representation (2014) 作者 J. Pennington et al. 句子和文档的分布式表示 Distributed representations of sentences and documents (2014) 作者Q. Le and T. Mikolov 词、短语及其合成性的分布式表征 Distributed representations of words and phrases and their compositionality (2013) 作者T. Mikolov et al. 有效评估词在向量空间中的表征 Efficient estimation of word representations in vector space (2013) 作者T. Mikolov et al. 基于情感树库应用于情感组合研究的递归深度网络模型 Recursive deep models for semantic compositionality over a sentiment treebank (2013) 作者R. Socher et al.
【文件预览】：
自然语言处理
----._Recursive deep models for semantic compositionality over a sentiment treebank (2013), R. Socher et al..pdf(4KB)
----._A character-level decoder without explicit segmentation for neural machine translation (2016), J. Chung et al..pdf(4KB)
----Exploring the limits of language modeling (2016), R. Jozefowicz et al..pdf(327KB)
----._Glove- Global vectors for word representation (2014), J. Pennington et al. .pdf(4KB)
----Efficient estimation of word representations in vector space (2013), T. Mikolov et al..pdf(223KB)
----Recursive deep models for semantic compositionality over a sentiment treebank (2013), R. Socher et al..pdf(1.25MB)
----._Convolutional neural networks for sentence classification (2014), Y. Kim.pdf(4KB)
----._Distributed representations of sentences and documents (2014), Q. Le and T. Mikolov.pdf(4KB)
----Convolutional neural networks for sentence classification (2014), Y. Kim.pdf(236KB)
----._Learning phrase representations using RNN encoder-decoder for statistical machine translation (2014), K. Cho et al. .pdf(4KB)
----._teaching-machines-to-read-and-comprehend.pdf(4KB)
----Neural machine translation by jointly learning to align and translate (2014), D. Bahdanau et al. .pdf(434KB)
----Glove- Global vectors for word representation (2014), J. Pennington et al. .pdf(2.54MB)
----._Sequence to sequence learning with neural networks (2014), I. Sutskever et al. .pdf(4KB)
----._Effective approaches to attention-based neural machine translation (2015), M. Luong et al..pdf(4KB)
----._A convolutional neural network for modelling sentences (2014), N. Kalchbrenner et al..pdf(4KB)
----._Neural machine translation by jointly learning to align and translate (2014), D. Bahdanau et al. .pdf(4KB)
----._Exploring the limits of language modeling (2016), R. Jozefowicz et al..pdf(4KB)
----._Efficient estimation of word representations in vector space (2013), T. Mikolov et al..pdf(4KB)
----Distributed representations of words and phrases and their compositionality (2013), T. Mikolov et al. .pdf(109KB)
----teaching-machines-to-read-and-comprehend.pdf(645KB)
----._Distributed representations of words and phrases and their compositionality (2013), T. Mikolov et al. .pdf(4KB)
----Effective approaches to attention-based neural machine translation (2015), M. Luong et al..pdf(244KB)
----A character-level decoder without explicit segmentation for neural machine translation (2016), J. Chung et al..pdf(671KB)
----A convolutional neural network for modelling sentences (2014), N. Kalchbrenner et al..pdf(417KB)
----Sequence to sequence learning with neural networks (2014), I. Sutskever et al. .pdf(140KB)
----Learning phrase representations using RNN encoder-decoder for statistical machine translation (2014), K. Cho et al. .pdf(1.09MB)
----Distributed representations of sentences and documents (2014), Q. Le and T. Mikolov.pdf(143KB)