148 search results - page 11 / 30 » Feature space perspectives for learning the kernel |
139
Voted
COLT
2003
Springer
15 years 9 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 ...
93
Voted
COLING
2010
14 years 10 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...
145
Voted
ALT
2004
Springer
16 years 18 days 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...
161
Voted
ML
2010
ACM
15 years 2 months 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...
145
Voted
ALT
2003
Springer
16 years 18 days 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 ...