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» Learning with Weighted Transducers
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ICASSP
2010
IEEE
13 years 9 months ago
Improved statistical models for SMT-based speaking style transformation
Automatic speech recognition (ASR) results contain not only ASR errors, but also disfluencies and colloquial expressions that must be corrected to create readable transcripts. We...
Graham Neubig, Yuya Akita, Shinsuke Mori, Tatsuya ...
IR
2006
13 years 9 months ago
Multilingual modeling of cross-lingual spelling variants
Technical term translations are important for cross-lingual information retrieval. In many languages, new technical terms have a common origin rendered with different spelling of ...
Krister Lindén
COLT
2005
Springer
14 years 2 months ago
Leaving the Span
We discuss a simple sparse linear problem that is hard to learn with any algorithm that uses a linear combination of the training instances as its weight vector. The hardness holds...
Manfred K. Warmuth, S. V. N. Vishwanathan
ICDM
2005
IEEE
151views Data Mining» more  ICDM 2005»
14 years 2 months ago
A Framework for Semi-Supervised Learning Based on Subjective and Objective Clustering Criteria
In this paper, we propose a semi-supervised framework for learning a weighted Euclidean subspace, where the best clustering can be achieved. Our approach capitalizes on user-const...
Maria Halkidi, Dimitrios Gunopulos, Nitin Kumar, M...
CSB
2004
IEEE
149views Bioinformatics» more  CSB 2004»
14 years 23 days ago
Weighting Features to Recognize 3D Patterns of Electron Density in X-Ray Protein Crystallography
Feature selection and weighting are central problems in pattern recognition and instance-based learning. In this work, we discuss the challenges of constructing and weighting feat...
Kreshna Gopal, Tod D. Romo, James C. Sacchettini, ...