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» On Classifier Domains of Competence
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ACL
2010
13 years 5 months ago
Creating Robust Supervised Classifiers via Web-Scale N-Gram Data
In this paper, we systematically assess the value of using web-scale N-gram data in state-of-the-art supervised NLP classifiers. We compare classifiers that include or exclude fea...
Shane Bergsma, Emily Pitler, Dekang Lin
IEEECGIV
2009
IEEE
14 years 2 months ago
Two Dimensional Compressive Classifier for Sparse Images
The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the ...
Armin Eftekhari, Hamid Abrishami Moghaddam, Massou...
DRR
2004
13 years 10 months ago
A nonparametric classifier for unsegmented text
Symbolic Indirect Correlation (SIC) is a new classification method for unsegmented patterns. SIC requires two levels of comparisons. First, the feature sequences from an unknown q...
George Nagy, Ashutosh Joshi, Mukkai S. Krishnamoor...
CVPR
2012
IEEE
11 years 10 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
ICML
2009
IEEE
14 years 8 months ago
Learning non-redundant codebooks for classifying complex objects
Codebook-based representations are widely employed in the classification of complex objects such as images and documents. Most previous codebook-based methods construct a single c...
Wei Zhang, Akshat Surve, Xiaoli Fern, Thomas G. Di...