904 search results - page 17 / 181 » Machine learning for stock selection |
CORR
2006
Springer
13 years 8 months ago
2006
Springer
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
ICML
2004
IEEE
14 years 2 months ago
2004
IEEE
This paper describes an e cient method for learning the parameters of a Gaussian process (GP). The parameters are learned from multiple tasks which are assumed to have been drawn ...
ICANN
2009
Springer
14 years 3 months ago
2009
Springer
This paper presents an application of multiple kernels like Kernel Basis to the Relevance Vector Machine algorithm. The framework of kernel machines has been a source of many works...
NIPS
1998
13 years 10 months ago
1998
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
NECO
2007
13 years 8 months ago
2007
Support Vector Machine (SVM) has been spotlighted in the machine learning community thanks to its theoretical soundness and practical performance. When applied to a large data set...