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» The Inefficiency of Batch Training for Large Training Sets
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IAT
2009
IEEE
14 years 3 months ago
An Intelligent Agent That Autonomously Learns How to Translate
—We describe the design of an autonomous agent that can teach itself how to translate from a foreign language, by first assembling its own training set, then using it to improve...
Marco Turchi, Tijl De Bie, Nello Cristianini
EMNLP
2009
13 years 6 months ago
Semi-supervised Semantic Role Labeling Using the Latent Words Language Model
Semantic Role Labeling (SRL) has proved to be a valuable tool for performing automatic analysis of natural language texts. Currently however, most systems rely on a large training...
Koen Deschacht, Marie-Francine Moens
NIPS
2007
13 years 10 months ago
Learning Bounds for Domain Adaptation
Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
John Blitzer, Koby Crammer, Alex Kulesza, Fernando...
ACL
2010
13 years 6 months ago
Practical Very Large Scale CRFs
Conditional Random Fields (CRFs) are a widely-used approach for supervised sequence labelling, notably due to their ability to handle large description spaces and to integrate str...
Thomas Lavergne, Olivier Cappé, Franç...
ICASSP
2009
IEEE
14 years 3 months ago
A study on multilingual acoustic modeling for large vocabulary ASR
We study key issues related to multilingual acoustic modeling for automatic speech recognition (ASR) through a series of large-scale ASR experiments. Our study explores shared str...
Hui Lin, Li Deng, Dong Yu, Yifan Gong, Alex Acero,...