Cross-Lingual Word Embeddings

Author:   Anders Sogaard ,  Ivan Vulic ,  Sebastian Ruder ,  Manaal Faruqui
Publisher:   Morgan & Claypool Publishers
ISBN:  

9781681730639


Pages:   132
Publication Date:   30 May 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Cross-Lingual Word Embeddings


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Author:   Anders Sogaard ,  Ivan Vulic ,  Sebastian Ruder ,  Manaal Faruqui
Publisher:   Morgan & Claypool Publishers
Imprint:   Morgan & Claypool Publishers
ISBN:  

9781681730639


ISBN 10:   1681730634
Pages:   132
Publication Date:   30 May 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Preface Introduction Monolingual Word Embedding Models Cross-Lingual Word Embedding Models: Typology A Brief History of Cross-Lingual Word Representations Word-Level Alignment Models Sentence-Level Alignment Methods Document-Level Alignment Models From Bilingual to Multilingual Training Unsupervised Learning of Cross-Lingual Word Embeddings Applications and Evaluation Useful Data and Software General Challenges and Future Directions Bibliography Authors' Biographies

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Author Information

Anders Sogaard is a Professor in Computer Science of the University of Copenhagen. He is funded by a Google Focused Research Award, and before that, he held an ERC Starting Grant. He has won best paper awards at NAACL, EACL, CoNLL, and more. He is interested in the learnability of language. Ivan Vulic is a Senior Research Associate in the Language Technology Lab at the University of Cambridge since 2015. Ivan holds a Ph.D. in Computer Science from KU Leuven, having achieved summa cum laude in 2014 on Unsupervised Algorithms for Cross-lingual Text Analysis, Translation Mining, and Information Retrieval. He is interested in representation learning, human language understanding, distributional, lexical, and multi-modal semantics in monolingual and multilingual contexts, and transfer learning for enabling cross-lingual NLP applications. He has co-authored more than 60 peer-reviewed research papers published in top-tier journals and conference proceedings in NLP and IR. He co-lectured a tutorial on monolingual and multilingual topic models and applications at ECIR 2013 and WSDM 2014, a tutorial on word vector space specialisation at EACL 2017 and ESSLLI 2018, a tutorial on cross lingual word representations at EMNLP 2017, and a tutorial on deep learning for conversational AI at NAACL 2018. Sebastian Ruder is a Research Scientist at DeepMind. He obtained his Ph.D. in Natural Language Processing at the National University of Ireland, Galway in 2019. He is interested in transfer learning and cross-lingual learning and has published widely read reviews as well as more than ten peer-reviewed research papers in top-tier conference proceedings in NLP. Manaal Faruqui is a Senior Research Scientist at Google, working on industrial scale NLP and ML problems. He obtained his Ph.D. in the Language Technologies Institute at Carnegie Mellon University while working on representation learning, multilingual learning, and distributional and lexical semantics. He received a best paper award at NAACL 2015 for his work on incorporating semantic knowledge in word vector representations. He serves on the editorial board of the Computational Linguistics journal and has been an area chair for several ACL conferences.

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