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GECCO
2003
Springer
153views Optimization» more  GECCO 2003»
15 years 2 months ago
SEPA: Structure Evolution and Parameter Adaptation in Feed-Forward Neural Networks
Abstract. In developing algorithms that dynamically changes the structure and weights of ANN (Artificial Neural Networks), there must be a proper balance between network complexit...
Paulito P. Palmes, Taichi Hayasaka, Shiro Usui
COMPLEXITY
2008
84views more  COMPLEXITY 2008»
14 years 9 months ago
Evolutionary learning of small networks
Results are presented of a simulation which mimics an evolutionary learning process for small networks. Special features of these networks include a high recurrency, a transition ...
Thomas Filk, Albrecht von Müller
76
Voted
RTSS
1999
IEEE
15 years 1 months ago
Parallel Switching in Connection-Oriented Networks
Packet switching in connection-oriented networks that may have multiple parallel links between pairs of switches is considered. An e cient packet-scheduling algorithm that guarant...
James H. Anderson, Sanjoy K. Baruah, Kevin Jeffay
NECO
2010
103views more  NECO 2010»
14 years 8 months ago
Posterior Weighted Reinforcement Learning with State Uncertainty
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
IJCNN
2006
IEEE
15 years 3 months ago
Learning using Dynamical Regime Identification and Synchronization
—This study proposes to generalize Hebbian learning by identifying and synchronizing the dynamical regimes of individual nodes in a recurrent network. The connection weights are ...
Nicolas Brodu