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NECO
2010
97views more  NECO 2010»
14 years 10 months ago
Rademacher Chaos Complexities for Learning the Kernel Problem
In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
Yiming Ying, Colin Campbell
ICPR
2004
IEEE
16 years 28 days ago
Joint Spatial and Temporal Structure Learning for Task based Control
We present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. We review work o...
Hilary Buxton, Kingsley Sage
DIS
2008
Springer
15 years 1 months ago
Active Learning for High Throughput Screening
Abstract. An important task in many scientific and engineering disciplines is to set up experiments with the goal of finding the best instances (substances, compositions, designs) ...
Kurt De Grave, Jan Ramon, Luc De Raedt
ECAI
2006
Springer
15 years 3 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani
CVPR
2009
IEEE
16 years 7 months ago
Learning Rotational Features for Filament Detection
State-of-the-art approaches for detecting filament-like structures in noisy images rely on filters optimized for signals of a particular shape, such as an ideal edge or ridge. W...
François Fleuret, Germán Gonzá...