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» Data selection for support vector machine classifiers
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NECO
2000
190views more  NECO 2000»
14 years 9 months ago
Generalized Discriminant Analysis Using a Kernel Approach
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
G. Baudat, Fatiha Anouar
ECAI
2008
Springer
14 years 11 months ago
WWW sits the SAT: Measuring Relational Similarity on the Web
Abstract. Measuring relational similarity between words is important in numerous natural language processing tasks such as solving analogy questions and classifying noun-modifier r...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...
IR
2010
14 years 7 months ago
Sentence-level event classification in unstructured texts
The ability to correctly classify sentences that describe events is an important task for many natural language applications such as Question Answering (QA) and Text Summarisation....
Martina Naughton, Nicola Stokes, Joe Carthy
ICANN
2009
Springer
14 years 7 months ago
MINLIP: Efficient Learning of Transformation Models
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
JMLR
2010
206views more  JMLR 2010»
14 years 4 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...