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» Using a Non-prior Training Active Feature Model
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EMNLP
2009
14 years 7 months ago
First- and Second-Order Expectation Semirings with Applications to Minimum-Risk Training on Translation Forests
Many statistical translation models can be regarded as weighted logical deduction. Under this paradigm, we use weights from the expectation semiring (Eisner, 2002), to compute fir...
Zhifei Li, Jason Eisner
ECCV
2004
Springer
15 years 11 months ago
A Linguistic Feature Vector for the Visual Interpretation of Sign Language
Abstract. This paper presents a novel approach to sign language recognition that provides extremely high classification rates on minimal training data. Key to this approach is a 2 ...
Richard Bowden, David Windridge, Timor Kadir, Andr...
NAACL
2004
14 years 10 months ago
Name Tagging with Word Clusters and Discriminative Training
We present a technique for augmenting annotated training data with hierarchical word clusters that are automatically derived from a large unannotated corpus. Cluster membership is...
Scott Miller, Jethran Guinness, Alex Zamanian
SDM
2010
SIAM
218views Data Mining» more  SDM 2010»
14 years 11 months ago
Confidence-Based Feature Acquisition to Minimize Training and Test Costs
We present Confidence-based Feature Acquisition (CFA), a novel supervised learning method for acquiring missing feature values when there is missing data at both training and test...
Marie desJardins, James MacGlashan, Kiri L. Wagsta...
IROS
2007
IEEE
158views Robotics» more  IROS 2007»
15 years 3 months ago
Feature selection in conditional random fields for activity recognition
Abstract— Temporal classification, such as activity recognition, is a key component for creating intelligent robot systems. In the case of robots, classification algorithms mus...
Douglas L. Vail, John D. Lafferty, Manuela M. Velo...