GLoMo: Unsupervised Learning of Transferable Relational Graphs
作者： Ruslan Salakhutdinov , Yann LeCun , William W. Cohen , Kaiming He , Bhuwan Dhingra
DOI:
关键词: Sentiment analysis 、 Artificial intelligence 、 Question answering 、 Natural language processing 、 Unsupervised learning 、 Contextual image classification 、 Word (computer architecture) 、 Computer science 、 Feature vector 、 Transfer of learning
摘要: Modern deep transfer learning approaches have mainly focused on learning generic feature vectors from one task that are transferable to other tasks, such as word embeddings in …
nips.cc参考文章(20)
Richard Socher, Andrew Y. Ng, Cliff C. Lin, Chris Manning, Parsing Natural Scenes and Natural Language with Recursive Neural Networks international conference on machine learning. pp. 129- 136 ,(2011)
Karen Simonyan, Andrew Zisserman, Very Deep Convolutional Networks for Large-Scale Image Recognition computer vision and pattern recognition. ,(2014)
Ali Sharif Razavian, Hossein Azizpour, Josephine Sullivan, Stefan Carlsson, CNN Features Off-the-Shelf: An Astounding Baseline for Recognition computer vision and pattern recognition. pp. 512- 519 ,(2014) , 10.1109/CVPRW.2014.131
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, Li Fei-Fei, ImageNet: A large-scale hierarchical image database computer vision and pattern recognition. pp. 248- 255 ,(2009) , 10.1109/CVPR.2009.5206848
Andrew Y. Ng, Christopher Potts, Andrew L. Maas, Dan Huang, Peter T. Pham, Raymond E. Daly, Learning Word Vectors for Sentiment Analysis meeting of the association for computational linguistics. pp. 142- 150 ,(2011)
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, Li Fei-Fei, ImageNet Large Scale Visual Recognition Challenge International Journal of Computer Vision. ,vol. 115, pp. 211- 252 ,(2015) , 10.1007/S11263-015-0816-Y
Ilya Sutskever, Tomas Mikolov, Greg S Corrado, Kai Chen, Jeff Dean, Distributed Representations of Words and Phrases and their Compositionality neural information processing systems. ,vol. 26, pp. 3111- 3119 ,(2013)
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Deep Residual Learning for Image Recognition computer vision and pattern recognition. pp. 770- 778 ,(2016) , 10.1109/CVPR.2016.90
Jeffrey Pennington, Richard Socher, Christopher Manning, Glove: Global Vectors for Word Representation empirical methods in natural language processing. pp. 1532- 1543 ,(2014) , 10.3115/V1/D14-1162
Richard Socher, Andrew Ng, Christopher Potts, Christopher D. Manning, Jason Chuang, Alex Perelygin, Jean Wu, Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank empirical methods in natural language processing. pp. 1631- 1642 ,(2013)