683 search results - page 3 / 137 » Generalization Bounds for Learning Kernels |
82
Voted
COLT
2007
Springer
15 years 5 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...
77
Voted
COLT
2008
Springer
15 years 1 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...
CORR
2010
Springer
14 years 6 months 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...
NIPS
2007
15 years 1 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...
97
Voted
COLT
2005
Springer
15 years 5 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...