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IJCNN
2006
IEEE
15 years 4 months ago
Generalization Improvement in Multi-Objective Learning
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Lars Gräning, Yaochu Jin, Bernhard Sendhoff
DAC
2007
ACM
15 years 2 months ago
Simultaneous Multi-Topology Multi-Objective Sizing Across Thousands of Analog Circuit Topologies
This paper presents MOJITO, a system which optimizes across thousands of analog circuit topologies simultaneously, and returns a set of sized topologies that collectively provide ...
Trent McConaghy, Pieter Palmers, Georges G. E. Gie...
EMO
2009
Springer
181views Optimization» more  EMO 2009»
15 years 3 months ago
Multi-Objective Particle Swarm Optimizers: An Experimental Comparison
Particle Swarm Optimization (PSO) has received increased attention in the optimization research community since its first appearance. Regarding multi-objective optimization, a con...
Juan José Durillo, José Garcí...
CEC
2007
IEEE
15 years 4 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...
GECCO
2009
Springer
107views Optimization» more  GECCO 2009»
15 years 5 months ago
Swarming along the evolutionary branches sheds light on genome rearrangement scenarios
A genome rearrangement scenario describes a series of chromosome fusion, fission, and translocation operations that suffice to rewrite one genome into another. Exact algorithmic ...
Nikolay Vyahhi, Adrien Goëffon, Macha Nikolsk...