Kernelized Hashcode Representations for Relation Extraction

10 Nov 2017Sahil GargAram GalstyanGreg Ver SteegIrina RishGuillermo CecchiShuyang Gao

Kernel methods have produced state-of-the-art results for a number of NLP tasks such as relation extraction, but suffer from poor scalability due to the high cost of computing kernel similarities between natural language structures. A recently proposed technique, kernelized locality-sensitive hashing (KLSH), can significantly reduce the computational cost, but is only applicable to classifiers operating on kNN graphs... (read more)

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