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IJCNN
2006
IEEE
15 years 6 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 4 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...
97
Voted
EMO
2009
Springer
181views Optimization» more  EMO 2009»
15 years 5 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...
97
Voted
CEC
2007
IEEE
15 years 6 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 ...
104
Voted
GECCO
2009
Springer
107views Optimization» more  GECCO 2009»
15 years 7 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...