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GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
14 years 2 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon
AAAI
2008
14 years 22 days ago
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning
This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...
CORR
2010
Springer
53views Education» more  CORR 2010»
13 years 10 months ago
Phase-Only Planar Antenna Array Synthesis with Fuzzy Genetic Algorithms
This paper describes a new method for the synthesis of planar antenna arrays using fuzzy genetic algorithms (FGAs) by optimizing phase excitation coefficients to best meet a desir...
Boufeldja Kadri, Miloud Boussahla, Fethi Tarik Ben...
CORR
2008
Springer
91views Education» more  CORR 2008»
13 years 10 months ago
Randomised Variable Neighbourhood Search for Multi Objective Optimisation
Various local search approaches have recently been applied to machine scheduling problems under multiple objectives. Their foremost consideration is the identification of the set ...
Martin Josef Geiger
IVS
2010
44views more  IVS 2010»
13 years 5 months ago
Generalized scatter plots
Scatter Plots are one of the most powerful and most widely used techniques for visual data exploration. A well-known problem is that scatter plots often have a high degree of overl...
Daniel A. Keim, Ming C. Hao, Umeshwar Dayal, Halld...