Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
A general regression technique for learning transductions
ICML '05 Proceedings of the 22nd international conference on Machine learning
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Kernel regression based machine translation
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Further meta-evaluation of machine translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
L1 regularized regression for reranking and system combination in machine translation
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
Instance selection for machine translation using feature decay algorithms
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
RegMT system for machine translation, system combination, and evaluation
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
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The novel kernel regression model for SMT only demonstrated encouraging results on small-scale toy data sets in previous works due to the complexities of kernel methods. It is the first time results based on the real-world data from the shared translation task will be reported at ACL 2008 Workshop on Statistical Machine Translation. This paper presents the key modules of our system, including the kernel ridge regression model, retrieval-based sparse approximation, the decoding algorithm, as well as language modeling issues under this framework.