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» Boosting Methods for Regression
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115
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BMCBI
2006
121views more  BMCBI 2006»
15 years 2 months ago
Robust computational reconstitution - a new method for the comparative analysis of gene expression in tissues and isolated cell
Background: Biological tissues consist of various cell types that differentially contribute to physiological and pathophysiological processes. Determining and analyzing cell type-...
Martin Hoffmann, Dirk Pohlers, Dirk Koczan, Hans-J...
117
Voted
ICTAI
2009
IEEE
15 years 9 months ago
Evolution Strategies for Constants Optimization in Genetic Programming
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
César Luis Alonso, José Luis Monta&n...
GECCO
2010
Springer
182views Optimization» more  GECCO 2010»
15 years 7 months ago
Model selection in genetic programming
Abstract. We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We pre...
Cruz E. Borges, César Luis Alonso, Jos&eacu...
122
Voted
ESANN
2006
15 years 4 months ago
Stochastic Processes for Canonical Correlation Analysis
We consider two stochastic process methods for performing canonical correlation analysis (CCA). The first uses a Gaussian Process formulation of regression in which we use the cur...
Colin Fyfe, Gayle Leen
232
Voted
ICDE
2008
IEEE
190views Database» more  ICDE 2008»
16 years 4 months ago
Efficient Query Processing in Large Traffic Networks
Abstract-- We present an original graph embedding to speedup distance-range and k-nearest neighbor queries on static and/or dynamic objects located on a (weighted) graph. Our metho...
Hans-Peter Kriegel, Matthias Renz, Peer Kröge...