When Are Tree Structures Necessary for Deep Learning of Representations? Jiwei Li1 , Minh-Thang Luong1 , Dan Jurafsky1 and Eduard Hovy2 Computer Science Department, Stanford University, Stanford, CALanguage Tech

First Page		Document Content
Date: 2015-10-31 15:44:36 Computational linguistics Linguistics Artificial neural networks Artificial intelligence Computational science Semantics Natural language processing Deep learning Recursive neural network Recurrent neural network Parsing Speech recognition		When Are Tree Structures Necessary for Deep Learning of Representations? Jiwei Li1 , Minh-Thang Luong1 , Dan Jurafsky1 and Eduard Hovy2 Computer Science Department, Stanford University, Stanford, CALanguage Tech Add to Reading List Source URL: nlp.stanford.edu Download Document from Source Website File Size: 324,04 KB Share Document on Facebook

	Using a Recursive Neural Network to Learn an Agent’s Decision Model for Plan Recognition Francis Bisson and Hugo Larochelle and Froduald Kabanza D´epartement d’informatique Universit´e de Sherbrooke Sherbrooke (QC) DocID: 1tQn7 - View Document
	PDF Document DocID: 1qyBA - View Document
	CS224d: Deep NLP Lecture 9: Wrap up: LSTMs and Recursive Neural Networks Richard Socher DocID: 1qwQT - View Document
	When Are Tree Structures Necessary for Deep Learning of Representations? Jiwei Li1 , Minh-Thang Luong1 , Dan Jurafsky1 and Eduard Hovy2 Computer Science Department, Stanford University, Stanford, CALanguage Tech DocID: 1pNCV - View Document
	Summarizing Source Code using a Neural Attention Model Srinivasan Iyer Ioannis Konstas Alvin Cheung Luke Zettlemoyer DocID: 1pDWG - View Document