148 search results - page 11 / 30 » Feature space perspectives for learning the kernel |
121
Voted
COLT
2003
Springer
15 years 7 months ago
2003
Springer
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
COLING
2010
14 years 8 months ago
2010
This paper proposes an efficient online method that trains a classifier with many conjunctive features. We employ kernel computation called kernel slicing, which explicitly consid...
125
click to vote
ALT
2004
Springer
15 years 10 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...
141
Voted
ML
2010
ACM
15 years 7 days ago
2010
ACM
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
131
click to vote
ALT
2003
Springer
15 years 10 months ago
2003
Springer
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...