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IJCNN
2007
IEEE
16 years 21 days ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
BMCBI
2005
125views more  BMCBI 2005»
15 years 6 months ago
A simple approach for protein name identification: prospects and limits
Background: Significant parts of biological knowledge are available only as unstructured text in articles of biomedical journals. By automatically identifying gene and gene produc...
Katrin Fundel, Daniel Güttler, Ralf Zimmer, J...
ECML
2004
Springer
15 years 11 months ago
Improving Random Forests
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
Marko Robnik-Sikonja
ICML
2008
IEEE
16 years 7 months ago
Large scale manifold transduction
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...
ICML
2003
IEEE
16 years 7 months ago
Transductive Learning via Spectral Graph Partitioning
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...
Thorsten Joachims