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» On Combining Classifiers
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EMNLP
2009
13 years 7 months ago
Polynomial to Linear: Efficient Classification with Conjunctive Features
This paper proposes a method that speeds up a classifier trained with many conjunctive features: combinations of (primitive) features. The key idea is to precompute as partial res...
Naoki Yoshinaga, Masaru Kitsuregawa
ACL
2009
13 years 8 months ago
Reducing the Annotation Effort for Letter-to-Phoneme Conversion
Letter-to-phoneme (L2P) conversion is the process of producing a correct phoneme sequence for a word, given its letters. It is often desirable to reduce the quantity of training d...
Kenneth Dwyer, Grzegorz Kondrak
DMIN
2009
142views Data Mining» more  DMIN 2009»
13 years 7 months ago
A Combinatorial Fusion Method for Feature Construction
- This paper demonstrates how methods borrowed from information fusion can improve the performance of a classifier by constructing (i.e., fusing) new features that are combinations...
Ye Tian, Gary M. Weiss, D. Frank Hsu, Qiang Ma
ECCV
2010
Springer
14 years 1 months ago
Efficient object category recognition using classemes
We introduce a new descriptor for images which allows the construction of efficient and compact classifiers with good accuracy on object category recognition. The descriptor is the...
ECCV
2010
Springer
14 years 2 days ago
Improving the Fisher Kernel for Large-Scale Image Classification
Abstract. The Fisher kernel (FK) is a generic framework which combines the benefits of generative and discriminative approaches. In the context of image classification the FK was s...