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GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
14 years 4 months ago
Techniques for highly multiobjective optimisation: some nondominated points are better than others
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much e...
David W. Corne, Joshua D. Knowles
GECCO
2010
Springer
230views Optimization» more  GECCO 2010»
14 years 3 months ago
Exponential natural evolution strategies
The family of natural evolution strategies (NES) offers a principled approach to real-valued evolutionary optimization by following the natural gradient of the expected fitness....
Tobias Glasmachers, Tom Schaul, Yi Sun, Daan Wiers...
GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
13 years 8 months ago
A multi-objective approach to data sharing with privacy constraints and preference based objectives
Public data sharing is utilized in a number of businesses to facilitate the exchange of information. Privacy constraints are usually enforced to prevent unwanted inference of info...
Rinku Dewri, Darrell Whitley, Indrajit Ray, Indrak...
ICML
1998
IEEE
14 years 11 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
GECCO
2007
Springer
256views Optimization» more  GECCO 2007»
14 years 4 months ago
A particle swarm optimization approach for estimating parameter confidence regions
Point estimates of the parameters in real world models convey valuable information about the actual system. However, parameter comparisons and/or statistical inference requires de...
Praveen Koduru, Stephen Welch, Sanjoy Das