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Multi-Task Learning for Multiple Language Translation
In this paper, we investigate the problem of learning a machine translation model that can simultaneously translate sentences from one source language to multiple target languages. Our solution isExpand
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Learning Semantic Hierarchies via Word Embeddings
Semantic hierarchy construction aims to build structures of concepts linked by hypernym‐hyponym (“is-a”) relations. A major challenge for this task is the automatic discovery of such relations. ThisExpand
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Pivot language approach for phrase-based statistical machine translation
  • Hua Wu, H. Wang
  • Computer Science
  • Machine Translation
  • 1 September 2007
This paper proposes a novel method for phrase-based statistical machine translation based on the use of a pivot language. To translate between languages Ls and Lt with limited bilingual resources, weExpand
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Cross-lingual Dependency Parsing Based on Distributed Representations
This paper investigates the problem of cross-lingual dependency parsing, aiming at inducing dependency parsers for low-resource languages while using only training data from a resource-rich languageExpand
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Revisiting Embedding Features for Simple Semi-supervised Learning
Recent work has shown success in using continuous word embeddings learned from unlabeled data as features to improve supervised NLP systems, which is regarded as a simple semi-supervised learningExpand
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A Representation Learning Framework for Multi-Source Transfer Parsing
Cross-lingual model transfer has been a promising approach for inducing dependency parsers for low-resource languages where annotated treebanks are not available. The major obstacles for the modelExpand
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Comparison of SVM and LS-SVM for Regression
  • H. Wang, D. Hu
  • Mathematics
  • International Conference on Neural Networks and…
  • 13 October 2005
Support vector machines (SVM) has been widely used in classification and nonlinear function estimation. However, the major drawback of SVM is its higher computational burden for the constrainedExpand
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Improved Neural Machine Translation with SMT Features
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and a target language decoder, making promising translation performance. However, as a newly emergedExpand
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Composition-based classification of short metagenomic sequences elucidates the landscapes of taxonomic and functional enrichment of microorganisms
Compared with traditional algorithms for long metagenomic sequence classification, characterizing microorganisms’ taxonomic and functional abundance based on tens of millions of very short reads areExpand
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Minimization of Transmission Loss in Meshed AC/DC Grids With VSC-MTDC Networks
The paper considers the optimal power flow (OPF) of a meshed AC/DC power transmission network with voltage source converter based multi-terminal DC (VSC-MTDC) networks. The OPF problem is formulatedExpand
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