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SEAL
2010
Springer
13 years 5 months ago
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
Ilya Loshchilov, Marc Schoenauer, Michèle S...
IJCNN
2006
IEEE
14 years 1 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
13 years 11 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
2006
Springer
170views Optimization» more  EMO 2006»
13 years 10 months ago
Robust Multi-Objective Optimization in High Dimensional Spaces
1 In most real world optimization problems several optimization goals have to be considered in parallel. For this reason, there has been a growing interest in Multi-Objective Optim...
André Sülflow, Nicole Drechsler, Rolf ...
HIS
2007
13 years 8 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin