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ICML
2007
IEEE
16 years 4 months ago
Optimal dimensionality of metric space for classification
In many real-world applications, Euclidean distance in the original space is not good due to the curse of dimensionality. In this paper, we propose a new method, called Discrimina...
Wei Zhang, Xiangyang Xue, Zichen Sun, Yue-Fei Guo,...
ICML
2008
IEEE
16 years 4 months ago
Graph kernels between point clouds
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
Francis R. Bach
133
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ICML
2002
IEEE
16 years 4 months ago
A New Statistical Approach to Personal Name Extraction
We propose a new statistical approach to extracting personal names from a corpus. One of the key points of our approach is that it can both automatically learn the characteristics...
Zheng Chen, Liu Wenyin, Feng Zhang
ICML
2002
IEEE
16 years 4 months ago
Diffusion Kernels on Graphs and Other Discrete Input Spaces
The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings. In this paper we propose a...
Risi Imre Kondor, John D. Lafferty
ICML
1999
IEEE
16 years 4 months ago
Approximation Via Value Unification
: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...
Paul E. Utgoff, David J. Stracuzzi