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JMLR
2010
61views more  JMLR 2010»
15 years 1 months ago
Model-based Boosting 2.0
This is an extended version of the manuscript Torsten Hothorn, Peter B
Torsten Hothorn, Peter Bühlmann, Thomas Kneib...
ICDM
2009
IEEE
155views Data Mining» more  ICDM 2009»
16 years 1 months ago
Stacked Gaussian Process Learning
—Triggered by a market relevant application that involves making joint predictions of pedestrian and public transit flows in urban areas, we address the question of how to utili...
Marion Neumann, Kristian Kersting, Zhao Xu, Daniel...
MICAI
2007
Springer
16 years 21 days ago
Weighted Instance-Based Learning Using Representative Intervals
Instance-based learning algorithms are widely used due to their capacity to approximate complex target functions; however, the performance of this kind of algorithms degrades signi...
Octavio Gómez, Eduardo F. Morales, Jes&uacu...
IJCNN
2006
IEEE
16 years 18 days ago
Bi-directional Modularity to Learn Visual Servoing Tasks
— This paper shows the advantage of using neural network modularity over conventional learning schemes to approximate complex functions. Indeed, it is difficult for artificial ...
Gilles Hermann, Patrice Wira, Jean-Philippe Urban
SIGECOM
2004
ACM
135views ECommerce» more  SIGECOM 2004»
15 years 12 months ago
Applying learning algorithms to preference elicitation
We consider the parallels between the preference elicitation problem in combinatorial auctions and the problem of learning an unknown function from learning theory. We show that l...
Sébastien Lahaie, David C. Parkes