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SEAL
2010
Springer
14 years 7 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
15 years 3 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 1 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»
15 years 1 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 ...
88
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HIS
2007
14 years 11 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