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PAMI
2011
15 years 1 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
EOR
2006
104views more  EOR 2006»
15 years 6 months ago
Link function selection in stochastic multicriteria decision making models
A stochastic formulation of the Analytic Hierarchy Process (AHP) using an approach based on Bayesian categorical data models has been developed. However, in categorical data model...
Eugene D. Hahn
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
15 years 12 months ago
Enhancing differential evolution performance with local search for high dimensional function optimization
In this paper, we proposed Fittest Individual Refinement (FIR), a crossover based local search method for Differential Evolution (DE). The FIR scheme accelerates DE by enhancing...
Nasimul Noman, Hitoshi Iba
ALGORITHMICA
2007
145views more  ALGORITHMICA 2007»
15 years 6 months ago
Counting Integer Points in Parametric Polytopes Using Barvinok's Rational Functions
Abstract Many compiler optimization techniques depend on the ability to calculate the number of elements that satisfy certain conditions. If these conditions can be represented by ...
Sven Verdoolaege, Rachid Seghir, Kristof Beyls, Vi...
JSW
2007
126views more  JSW 2007»
15 years 6 months ago
On Remote and Virtual Experiments in eLearning
— The science of physics is based on theories and models as well as experiments: the former structure relations and simplify reality to a degree such that predictions on physical...
Sabina Jeschke, Harald Scheel, Thomas Richter, Chr...