Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs

NeurIPS 2012 Michael CollinsShay B. Cohen

We describe an approach to speed-up inference with latent variable PCFGs, which have been shown to be highly effective for natural language parsing. Our approach is based on a tensor formulation recently introduced for spectral estimation of latent-variable PCFGs coupled with a tensor decomposition algorithm well-known in the multilinear algebra literature... (read more)

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