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ACL
1998
13 years 10 months ago
Automatic Acquisition of Hierarchical Transduction Models for Machine Translation
We describe a method for the fully automatic learning of hierarchical finite state translation models. The input to the method is transcribed speech utterances and their correspon...
Hiyan Alshawi, Srinivas Bangalore, Shona Douglas
COLING
2002
13 years 8 months ago
Extracting Word Sequence Correspondences with Support Vector Machines
This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support Vector Machines, which have high ability of th...
Kengo Sato, Hiroaki Saito
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
15 years 4 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
ACL
2006
13 years 10 months ago
Modeling Commonality among Related Classes in Relation Extraction
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
Guodong Zhou, Jian Su, Min Zhang
COLING
2010
13 years 4 months ago
Adaptive Development Data Selection for Log-linear Model in Statistical Machine Translation
This paper addresses the problem of dynamic model parameter selection for loglinear model based statistical machine translation (SMT) systems. In this work, we propose a principle...
Mu Li, Yinggong Zhao, Dongdong Zhang, Ming Zhou