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NN
2000
Springer
167views Neural Networks» more  NN 2000»
15 years 1 months ago
Blind signal processing by the adaptive activation function neurons
The aim of this paper is to study an Information Theory based learning theory for neural units endowed with adaptive activation functions. The learning theory has the target to fo...
Simone Fiori
107
Voted
ATAL
2010
Springer
15 years 3 months ago
Evolving policy geometry for scalable multiagent learning
A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
110
Voted
GECCO
2004
Springer
211views Optimization» more  GECCO 2004»
15 years 7 months ago
Adaptive and Evolvable Network Services
This paper proposes an evolutionary framework where a network service is created from a group of autonomous agents that interact and evolve. Agents in our framework are capable of ...
Tadashi Nakano, Tatsuya Suda
106
Voted
FPGA
2009
ACM
201views FPGA» more  FPGA 2009»
15 years 8 months ago
A high-performance FPGA architecture for restricted boltzmann machines
Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications have been limited. A primary cause of this lack of...
Daniel L. Ly, Paul Chow
117
Voted
ECAL
2003
Springer
15 years 7 months ago
Evolving Fractal Gene Regulatory Networks for Robot Control
Fractal proteins are a new evolvable method of mapping genotype to phenotype through a developmental process, where genes are expressed into proteins comprised of subsets of the Ma...
Peter J. Bentley