106 search results - page 9 / 22 » A generalization of Haussler's convolution kernel: mapping k... |
ML
2008
ACM
13 years 5 months ago
2008
ACM
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
SIPS
2008
IEEE
14 years 1 months ago
2008
IEEE
Low-density parity-check (LDPC) codes on par with convolutional turbo codes (CTC) are two of the most powerful error correction codes known to perform very close to the Shannon li...
TCS
2008
13 years 7 months ago
2008
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
ECCV
2010
Springer
13 years 11 months ago
2010
Springer
Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear sim...
NIPS
2008
13 years 8 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...