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IJCNN
2007
IEEE
14 years 1 months ago
Generalised Kernel Machines
Abstract— The generalised linear model (GLM) is the standard approach in classical statistics for regression tasks where it is appropriate to measure the data misfit using a lik...
Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. T...
JC
2006
68views more  JC 2006»
13 years 7 months ago
Monte Carlo approximation of weakly singular integral operators
We study the randomized approximation of weakly singular integral operators. For a suitable class of kernels having a standard type of singularity and being otherwise of finite sm...
Stefan Heinrich
ALT
2004
Springer
14 years 4 months ago
On Kernels, Margins, and Low-Dimensional Mappings
Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability to gain much of the power of that space without inc...
Maria-Florina Balcan, Avrim Blum, Santosh Vempala
ECCV
2010
Springer
13 years 7 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
ICML
2006
IEEE
14 years 8 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil