John Shawe-Taylor


2018

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Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding
Gaurav Singh | James Thomas | Iain Marshall | John Shawe-Taylor | Byron C. Wallace
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

We propose a model for tagging unstructured texts with an arbitrary number of terms drawn from a tree-structured vocabulary (i.e., an ontology). We treat this as a special case of sequence-to-sequence learning in which the decoder begins at the root node of an ontological tree and recursively elects to expand child nodes as a function of the input text, the current node, and the latent decoder state. We demonstrate that this method yields state-of-the-art results on the important task of assigning MeSH terms to biomedical abstracts.

2009

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Large-margin structural prediction via linear programming
Zuoran Wang | John Shawe-Taylor | Sándor Szedmák
Proceedings of the 13th Annual conference of the European Association for Machine Translation

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Sentence-level confidence estimation for MT
Lucia Specia | Nicola Cancedda | Marc Dymetman | Craig Saunders | Marco Turchi | Nello Cristianini | Zhuoran Wang | John Shawe-Taylor
Proceedings of the 13th Annual conference of the European Association for Machine Translation

2008

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Kernel Regression Framework for Machine Translation: UCL System Description for WMT 2008 Shared Translation Task
Zhuoran Wang | John Shawe-Taylor
Proceedings of the Third Workshop on Statistical Machine Translation

2007

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Kernel Regression Based Machine Translation
Zhuoran Wang | John Shawe-Taylor | Sandor Szedmak
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers

2003

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The SVM With Uneven Margins and Chinese Document Categorization
Yaoyong Li | John Shawe-Taylor
Proceedings of the 17th Pacific Asia Conference on Language, Information and Computation