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ICML
2005
IEEE
14 years 11 months ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer
ICMLA
2009
13 years 7 months ago
Improving Clinical Relevance in Ensemble Support Vector Machine Models of Radiation Pneumonitis Risk
Patients undergoing thoracic radiation therapy can develop radiation pneumonitis (RP), a potentially fatal inflammation of the lungs. Support vector machines (SVMs), a statistical...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...
ICML
2006
IEEE
14 years 11 months ago
Simpler knowledge-based support vector machines
If appropriately used, prior knowledge can significantly improve the predictive accuracy of learning algorithms or reduce the amount of training data needed. In this paper we intr...
Quoc V. Le, Alex J. Smola, Thomas Gärtner
FPL
2009
Springer
156views Hardware» more  FPL 2009»
14 years 2 months ago
A highly scalable Restricted Boltzmann Machine FPGA implementation
Restricted Boltzmann Machines (RBMs) — the building block for newly popular Deep Belief Networks (DBNs) — are a promising new tool for machine learning practitioners. However,...
Sang Kyun Kim, Lawrence C. McAfee, Peter L. McMaho...
ICML
2007
IEEE
14 years 11 months ago
A kernel path algorithm for support vector machines
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky