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ICPR
2008
IEEE
16 years 1 months ago
A supervised learning approach for imbalanced data sets
This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resamp...
Giang Hoang Nguyen, Abdesselam Bouzerdoum, Son Lam...
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
15 years 7 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu
EMO
2006
Springer
161views Optimization» more  EMO 2006»
15 years 10 months ago
Design Issues in a Multiobjective Cellular Genetic Algorithm
In this paper we study a number of issues related to the design of a cellular genetic algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm fol...
Antonio J. Nebro, Juan José Durillo, Franci...
ICML
2006
IEEE
16 years 7 months ago
A DC-programming algorithm for kernel selection
We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
IEEEPACT
2002
IEEE
15 years 11 months ago
Exploiting Pseudo-Schedules to Guide Data Dependence Graph Partitioning
This paper presents a new modulo scheduling algorithm for clustered microarchitectures. The main feature of the proposed scheme is that the assignment of instructions to clusters ...
Alex Aletà, Josep M. Codina, F. Jesú...