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ML
2000
ACM
244views Machine Learning» more  ML 2000»
15 years 1 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski
APIN
1999
114views more  APIN 1999»
15 years 1 months ago
Evolutionary Approaches to Figure-Ground Separation
The problem of figure-ground separation is tackled from the perspective of combinatorial optimization. Previous attempts have used deterministic optimization techniques based on re...
Suchendra M. Bhandarkar, Xia Zeng
TFS
2008
157views more  TFS 2008»
15 years 1 months ago
Efficient Self-Evolving Evolutionary Learning for Neurofuzzy Inference Systems
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
Cheng-Jian Lin, Cheng-Hung Chen, Chin-Teng Lin
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
15 years 7 months ago
Reducing the number of transistors in digital circuits using gate-level evolutionary design
This paper shows that the evolutionary design of digital circuits which is conducted at the gate level is able to produce human-competitive circuits at the transistor level. In ad...
Zbysek Gajda, Lukás Sekanina
141
Voted
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 7 months ago
Observing the swarm behaviour during its evolutionary design
Evolutionary Algorithms (EAs) can be used for designing Particle Swarm Optimization (PSO) algorithms that work, in some cases, considerably better than the human-designed ones. By...
Laura Diosan, Mihai Oltean