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144
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SDM
2012
SIAM
13 years 3 months ago
2012
SIAM
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
AAAI
2010
15 years 2 months ago
2010
Multiple Kernel Learning (MKL) can be formulated as a convex-concave minmax optimization problem, whose saddle point corresponds to the optimal solution to MKL. Most MKL methods e...
150
Voted
DAGM
2011
Springer
14 years 14 days ago
2011
Springer
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
96
Voted
ICIP
2003
IEEE
16 years 2 months ago
2003
IEEE
In this paper we address the problem of classifying images, by exploiting global features that describe color and illumination properties, and by using the statistical learning pa...
115
Voted
MLDM
2007
Springer
15 years 6 months ago
2007
Springer
In this paper we propose a new criterion, based on Minimum Description Length (MDL), to estimate an optimal number of clusters. This criterion, called Kernel MDL (KMDL), is particu...