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» Generalization Improvement in Multi-Objective Learning
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96
Voted
ICDM
2010
IEEE
178views Data Mining» more  ICDM 2010»
14 years 10 months ago
Exploiting Unlabeled Data to Enhance Ensemble Diversity
Ensemble learning aims to improve generalization ability by using multiple base learners. It is well-known that to construct a good ensemble, the base learners should be accurate a...
Min-Ling Zhang, Zhi-Hua Zhou
ICML
2009
IEEE
16 years 1 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
SIGCSE
2006
ACM
172views Education» more  SIGCSE 2006»
15 years 6 months ago
Computing in context: integrating an embedded computing project into a course on ethical and societal issues
A hands-on embedded computing project is introduced into an undergraduate social sciences course. In the pilot module, nine student teams created working prototypes, using the tec...
Fred G. Martin, Sarah Kuhn
96
Voted
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
15 years 1 months ago
Recursive least squares and quadratic prediction in continuous multistep problems
XCS with computed prediction, namely XCSF, has been recently extended in several ways. In particular, a novel prediction update algorithm based on recursive least squares and the ...
Daniele Loiacono, Pier Luca Lanzi
COLT
2000
Springer
15 years 4 months ago
PAC Analogues of Perceptron and Winnow via Boosting the Margin
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Rocco A. Servedio