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GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
14 years 2 days ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
PPSN
2004
Springer
14 years 24 days ago
Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
KES
2008
Springer
13 years 7 months ago
Instruction-based development: From evolution to generic structures of digital circuits
Evolutionary techniques provide powerful tools to design novel solutions for hard problems in different areas. However, the problem of scale (i.e. how to create a large, complex s...
Michal Bidlo, Jaroslav Skarvada
GECCO
2007
Springer
276views Optimization» more  GECCO 2007»
14 years 1 months ago
Meta-optimizing semantic evolutionary search
I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution. Distributions are not esti...
Moshe Looks
AAAI
2000
13 years 8 months ago
Applying Learnable Evolution Model to Heat Exchanger Design
A new approach to evolutionary computation, called Learnable Evolution Model (LEM), has been applied to the problem of optimizing tube structures of heat exchangers. In contrast t...
Kenneth A. Kaufman, Ryszard S. Michalski