44 search results - page 5 / 9 » On numerical optimization theory of infinite kernel learning |
COLT
2004
Springer
15 years 4 months ago
2004
Springer
Abstract. The Gram matrix plays a central role in many kernel methods. Knowledge about the distribution of eigenvalues of the Gram matrix is useful for developing appropriate model...
PAA
2010
14 years 9 months ago
2010
By applying recent results in optimization theory variously known as optimization transfer or majorize/minimize algorithms, an algorithm for binary, kernel, Fisher discriminant ana...
ICML
2005
IEEE
15 years 12 months ago
2005
IEEE
The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...
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NIPS
2000
15 years 15 days ago
2000
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
MLG
2007
Springer
15 years 5 months ago
2007
Springer
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...