4 search results - page 1 / 1 » Dimension and Margin Bounds for Reflection-invariant Kernels |
134
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COLT
2008
Springer
15 years 7 months ago
2008
Springer
A kernel over the Boolean domain is said to be reflection-invariant, if its value does not change when we flip the same bit in both arguments. (Many popular kernels have this prop...
169
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ALT
2004
Springer
16 years 2 months ago
2004
Springer
Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability to gain much of the power of that space without inc...
180
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COLT
1999
Springer
15 years 10 months ago
1999
Springer
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
192
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COLT
2010
Springer
15 years 3 months ago
2010
Springer
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...