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ANLP
1994
98views more  ANLP 1994»
15 years 1 months ago
Combination of Symbolic and Statistical Approaches for Grammatical Knowledge Acquisition
The framework we adopted for customizing linguistic knowledge to individual application domains is an integration of symbolic and statistical approaches. In order to acquire domai...
Masaki Kiyono, Jun-ichi Tsujii
IJHPCA
2008
104views more  IJHPCA 2008»
15 years 16 days ago
Low-Complexity Principal Component Analysis for Hyperspectral Image Compression
Principal component analysis (PCA) is an effective tool for spectral decorrelation of hyperspectral imagery, and PCA-based spectral transforms have been employed successfully in co...
Qian Du, James E. Fowler
85
Voted
IJON
2000
71views more  IJON 2000»
15 years 10 days ago
Variable selection using neural-network models
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...
Giovanna Castellano, Anna Maria Fanelli
MOC
2000
124views more  MOC 2000»
15 years 9 days ago
Local and parallel finite element algorithms based on two-grid discretizations
A number of new local and parallel discretization and adaptive finite element algorithms are proposed and analyzed in this paper for elliptic boundary value problems. These algorit...
Jinchao Xu, Aihui Zhou
108
Voted
NN
2000
Springer
161views Neural Networks» more  NN 2000»
15 years 9 days ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys