683 search results - page 3 / 137 » Generalization Bounds for Learning Kernels |
140
Voted
COLT
2007
Springer
15 years 12 months ago
2007
Springer
Recently, Balcan and Blum [1] suggested a theory of learning based on general similarity functions, instead of positive semi-definite kernels. We study the gap between the learnin...
135
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COLT
2008
Springer
15 years 7 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...
150
Voted
CORR
2010
Springer
15 years 23 days ago
2010
Springer
Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different for...
143
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NIPS
2007
15 years 7 months ago
2007
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...
159
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COLT
2005
Springer
15 years 11 months ago
2005
Springer
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...