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» Kernels for Semi-Structured Data
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128
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ACL
2006
15 years 4 months ago
Using String-Kernels for Learning Semantic Parsers
We present a new approach for mapping natural language sentences to their formal meaning representations using stringkernel-based classifiers. Our system learns these classifiers ...
Rohit J. Kate, Raymond J. Mooney
150
Voted
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 3 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
140
Voted
ICCV
2009
IEEE
16 years 7 months ago
Constrained Clustering by Spectral Kernel Learning
Clustering performance can often be greatly improved by leveraging side information. In this paper, we consider constrained clustering with pairwise constraints, which specify s...
Zhenguo Li, Jianzhuang Liu
107
Voted
ICIP
2006
IEEE
16 years 4 months ago
Estimating Illumination Chromaticity via Kernel Regression
We propose a simple nonparametric linear regression tool, known as kernel regression (KR), to estimate the illumination chromaticity. We design a Gaussian kernel whose bandwidth i...
Vivek Agarwal, Andrei V. Gribok, Andreas Koschan, ...
103
Voted
ICIP
1999
IEEE
16 years 4 months ago
The Sinc-Approximating Kernels of Classical Polynomial Interpolation
A classical approach to interpolation of sampled data is polynomial interpolation. However, from the sampling theorem it follows that the ideal approach to interpolation is to con...
Erik H. W. Meijering, Wiro J. Niessen, Max A. Vier...