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» Boosting Methods for Regression
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ICML
2005
IEEE
14 years 11 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers
WSOM
2009
Springer
14 years 4 months ago
Towards Semi-supervised Manifold Learning: UKR with Structural Hints
We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-su...
Jan Steffen, Stefan Klanke, Sethu Vijayakumar, Hel...
ESANN
2008
13 years 11 months ago
Direct and inverse solution for a stimulus adaptation problem using SVR
Adapting stimuli to stabilize neural responses is an important problem in the context of cortical prostheses. This paper describes two approaches for stimulus adaptation using supp...
Dominik Brugger, Sergejus Butovas, Martin Bogdan, ...
EUSFLAT
2003
108views Fuzzy Logic» more  EUSFLAT 2003»
13 years 11 months ago
Soft computing and control of district heating system
The article deals with the possible methodology of processing of data and information for the search of prediction of heat supply daily diagram (HSDD). The methodology includes te...
Petr Dostál, Bronislav Chramcov, Jaroslav B...
JMLR
2002
75views more  JMLR 2002»
13 years 9 months ago
Stability and Generalization
We define notions of stability for learning algorithms and show how to use these notions to derive generalization error bounds based on the empirical error and the leave-one-out e...
Olivier Bousquet, André Elisseeff