137 search results - page 2 / 28 » Quantifying the Impact of Learning Algorithm Parameter Tunin... |
ICANN
2007
Springer
13 years 11 months ago
2007
Springer
This paper proposes a novel approach for directly tuning the gaussian kernel matrix for one class learning. The popular gaussian kernel includes a free parameter, σ, that requires...
CP
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
HIS
2008
13 years 6 months ago
2008
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
ALT
2007
Springer
14 years 2 months ago
2007
Springer
Algorithms based on upper-confidence bounds for balancing exploration and exploitation are gaining popularity since they are easy to implement, efficient and effective. In this p...
ICMLA
2009
13 years 3 months ago
2009
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...