648 search results - page 7 / 130 » A general dimension for query learning |
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...
COLT
1993
Springer
13 years 11 months ago
1993
Springer
The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis of learning problems in the PAC framework. For polynomial learnability, we seek upper bou...
COLT
2008
Springer
13 years 9 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...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
STACS
2005
Springer
14 years 1 months ago
2005
Springer
In property testing, we are given oracle access to a function f, and we wish to test if the function satisfies a given property P, or it is ε-far from having that property. In a...