1334 search results - page 53 / 267 » Composite kernel learning |
136
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NIPS
2004
15 years 4 months ago
2004
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
137
Voted
CORR
2006
Springer
15 years 3 months ago
2006
Springer
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
106
Voted
ESWS
2007
Springer
15 years 9 months ago
2007
Springer
Abstract. In this paper we propose an algorithm for personalized learning based on a user’s query and a repository of lecture subparts —i.e., learning objects— both are descr...
ALT
2002
Springer
16 years 2 days ago
2002
Springer
Abstract. In this paper we analyze the relationships between the eigenvalues of the m × m Gram matrix K for a kernel k(·, ·) corresponding to a sample x1, . . . , xm drawn from ...
142
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ML
2002
ACM
15 years 2 months ago
2002
ACM
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...