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Embedding Text in Hyperbolic Spaces
2018
Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-12)
Natural language text exhibits hierarchical structure in a variety of respects. Ideally, we could incorporate our prior knowledge of this hierarchical structure into unsupervised learning algorithms that work on text data. Recent work by Nickel and Kiela (2017) proposed using hyperbolic instead of Euclidean embedding spaces to represent hierarchical data and demonstrated encouraging results when embedding graphs. In this work, we extend their method with a re-parameterization technique that
doi:10.18653/v1/w18-1708
dblp:conf/textgraphs/DhingraSNDD18
fatcat:xmfgkg7jg5fhpnk2qv2zi6wk5q