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134
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IJCNN
2008
IEEE
15 years 11 months ago
Sparse kernel density estimator using orthogonal regression based on D-Optimality experimental design
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
Sheng Chen, Xia Hong, Chris J. Harris
142
Voted
IJCNN
2008
IEEE
15 years 11 months ago
A formula of equations of states in singular learning machines
Abstract— Almost all learning machines used in computational intelligence are not regular but singular statistical models, because they are nonidentifiable and their Fisher info...
Sumio Watanabe
165
Voted
IJCNN
2008
IEEE
15 years 11 months ago
Sparse support vector machines trained in the reduced empirical feature space
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
Kazuki Iwamura, Shigeo Abe
IJCNN
2008
IEEE
15 years 11 months ago
Kernel methods for fMRI pattern prediction
Abstract— In this paper, we present an effective computational approach for learning patterns of brain activity from the fMRI data. The procedure involved correcting motion artif...
Yizhao Ni, Carlton Chu, Craig J. Saunders, John As...
IJCNN
2008
IEEE
15 years 11 months ago
Spatiotemporal feature extraction based on invariance representation
— This paper investigates spatiotemporal feature extraction from temporal image sequences based on invariance representation. Invariance representation is one of important functi...
Wenlu Yang, Liqing Zhang