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103
Voted
ML
2000
ACM
244views Machine Learning» more  ML 2000»
14 years 10 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
88
Voted
APIN
1999
114views more  APIN 1999»
14 years 9 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
126
Voted
TFS
2008
157views more  TFS 2008»
14 years 9 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
102
Voted
ASC
2011
14 years 5 months ago
Quality of Service constrained routing optimization using Evolutionary Computation
In this work, a novel optimization framework is proposed that allows the improvement of Quality of Service levels in TCP/IP based networks, by configuring the routing weights of ...
Miguel Rocha, Pedro Sousa, Paulo Cortez, Miguel Ri...
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
15 years 4 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