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» Relation Extraction Using Support Vector Machine
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COLT
2004
Springer
15 years 8 months ago
Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results
One of the nice properties of kernel classifiers such as SVMs is that they often produce sparse solutions. However, the decision functions of these classifiers cannot always be u...
Peter L. Bartlett, Ambuj Tewari
DIS
2008
Springer
15 years 5 months ago
String Kernels Based on Variable-Length-Don't-Care Patterns
Abstract. We propose a new string kernel based on variable-lengthdon't-care patterns (VLDC patterns). A VLDC pattern is an element of ({}) , where is an alphabet and is the ...
Kazuyuki Narisawa, Hideo Bannai, Kohei Hatano, Shu...
ESANN
2008
15 years 4 months ago
GeoKernels: modeling of spatial data on geomanifolds
This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental ...
Alexei Pozdnoukhov, Mikhail F. Kanevski
NIPS
2000
15 years 4 months ago
The Kernel Trick for Distances
A method is described which, like the kernel trick in support vector machines (SVMs), lets us generalize distance-based algorithms to operate in feature spaces, usually nonlinearl...
Bernhard Schölkopf
AAAI
2004
15 years 4 months ago
Just How Mad Are You? Finding Strong and Weak Opinion Clauses
There has been a recent swell of interest in the automatic identification and extraction of opinions and emotions in text. In this paper, we present the first experimental results...
Theresa Wilson, Janyce Wiebe, Rebecca Hwa